Datasets:
pwc-archive
/
links-between-paper-and-code

Dataset card Data Studio Files
xet
Community
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https://paperswithcode.com/paper/survival-extinction-and-interface-stability
Survival, extinction, and interface stability in a two--phase moving boundary model of biological invasion
2306.15379
https://arxiv.org/abs/2306.15379v3
https://arxiv.org/pdf/2306.15379v3.pdf
https://github.com/alex-tam/twophaseinvasion
true
true
false
none
https://paperswithcode.com/paper/use-of-speaker-recognition-approaches-for
Use of speaker recognition approaches for learning and evaluating embedding representations of musical instrument sounds
2107.11506
https://arxiv.org/abs/2107.11506v2
https://arxiv.org/pdf/2107.11506v2.pdf
https://github.com/Alexuan/musical_instrument_embedding
true
true
false
pytorch
https://paperswithcode.com/paper/unsupervised-pretraining-transfers-well
Unsupervised pretraining transfers well across languages
2002.02848
https://arxiv.org/abs/2002.02848v1
https://arxiv.org/pdf/2002.02848v1.pdf
https://github.com/chorowski-lab/hcpc
false
false
true
pytorch
https://paperswithcode.com/paper/variable-rate-hierarchical-cpc-leads-to
Variable-rate hierarchical CPC leads to acoustic unit discovery in speech
2206.02211
https://arxiv.org/abs/2206.02211v3
https://arxiv.org/pdf/2206.02211v3.pdf
https://github.com/chorowski-lab/hcpc
true
true
true
pytorch
https://paperswithcode.com/paper/self-supervised-contrastive-learning-for
Self-Supervised Contrastive Learning for Unsupervised Phoneme Segmentation
2007.13465
https://arxiv.org/abs/2007.13465v2
https://arxiv.org/pdf/2007.13465v2.pdf
https://github.com/chorowski-lab/hcpc
false
false
true
pytorch
https://paperswithcode.com/paper/accelerating-deep-reinforcement-learning-of
Accelerating Deep Reinforcement Learning of Active Flow Control strategies through a multi-environment approach
1906.10382
https://arxiv.org/abs/1906.10382v1
https://arxiv.org/pdf/1906.10382v1.pdf
https://github.com/jerabaul29/Cylinder2DFlowControlDRLParallel
true
true
true
none
https://paperswithcode.com/paper/artificial-neural-networks-trained-through
Artificial Neural Networks trained through Deep Reinforcement Learning discover control strategies for active flow control
1808.07664
http://arxiv.org/abs/1808.07664v5
http://arxiv.org/pdf/1808.07664v5.pdf
https://github.com/jerabaul29/Cylinder2DFlowControlDRLParallel
false
false
true
none
https://paperswithcode.com/paper/the-utility-of-explainable-ai-in-ad-hoc-human-1
The Utility of Explainable AI in Ad Hoc Human-Machine Teaming
2209.03943
https://arxiv.org/abs/2209.03943v1
https://arxiv.org/pdf/2209.03943v1.pdf
https://github.com/CORE-Robotics-Lab/Utility-of-Explainable-AI-NeurIPS2021
true
false
false
none
https://paperswithcode.com/paper/decorrelate-irrelevant-purify-relevant
Decorrelate Irrelevant, Purify Relevant: Overcome Textual Spurious Correlations from a Feature Perspective
2202.08048
https://arxiv.org/abs/2202.08048v2
https://arxiv.org/pdf/2202.08048v2.pdf
https://github.com/coling2022-depro/depro
true
true
false
pytorch
https://paperswithcode.com/paper/fdnerf-few-shot-dynamic-neural-radiance
FDNeRF: Few-shot Dynamic Neural Radiance Fields for Face Reconstruction and Expression Editing
2208.05751
https://arxiv.org/abs/2208.05751v2
https://arxiv.org/pdf/2208.05751v2.pdf
https://github.com/fdnerf/fdnerf
true
true
false
pytorch
https://paperswithcode.com/paper/deep-stable-learning-for-out-of-distribution
Deep Stable Learning for Out-Of-Distribution Generalization
2104.07876
https://arxiv.org/abs/2104.07876v1
https://arxiv.org/pdf/2104.07876v1.pdf
https://github.com/coling2022-depro/depro
false
false
true
pytorch
https://paperswithcode.com/paper/patching-weak-convolutional-neural-network
Patching Weak Convolutional Neural Network Models through Modularization and Composition
2209.06116
https://arxiv.org/abs/2209.06116v3
https://arxiv.org/pdf/2209.06116v3.pdf
https://github.com/qibinhang/cnnsplitter
true
true
false
pytorch
https://paperswithcode.com/paper/glm-130b-an-open-bilingual-pre-trained-model
GLM-130B: An Open Bilingual Pre-trained Model
2210.02414
https://arxiv.org/abs/2210.02414v2
https://arxiv.org/pdf/2210.02414v2.pdf
https://github.com/2023-MindSpore-4/Code12/tree/main/MindFormers/glm
false
false
false
mindspore
https://paperswithcode.com/paper/a-practical-calibration-method-for-rgb-micro
A Practical Calibration Method for RGB Micro-Grid Polarimetric Cameras
2208.13485
https://arxiv.org/abs/2208.13485v1
https://arxiv.org/pdf/2208.13485v1.pdf
https://github.com/vibot-lab/policalibration
true
true
true
none
https://paperswithcode.com/paper/joingym-an-efficient-query-optimization
JoinGym: An Efficient Query Optimization Environment for Reinforcement Learning
2307.11704
https://arxiv.org/abs/2307.11704v2
https://arxiv.org/pdf/2307.11704v2.pdf
https://github.com/kaiwenw/JoinGym
true
true
false
pytorch
https://paperswithcode.com/paper/a-pixelated-approach-to-galaxy-catalogue
A Pixelated Approach to Galaxy Catalogue Incompleteness: Improving the Dark Siren Measurement of the Hubble Constant
2111.04629
https://arxiv.org/abs/2111.04629v2
https://arxiv.org/pdf/2111.04629v2.pdf
https://github.com/mariapalfi/gwcosmo_coasting
false
false
true
none
https://paperswithcode.com/paper/evidence-definitions-and-algorithms-regarding
Evidence, Definitions and Algorithms regarding the Existence of Cohesive-Convergence Groups in Neural Network Optimization
2403.05610
https://arxiv.org/abs/2403.05610v1
https://arxiv.org/pdf/2403.05610v1.pdf
https://github.com/thienannguyen-cv/Experiments-of-Cohesive-Convergence-Group
true
false
false
pytorch
https://paperswithcode.com/paper/correlation-without-factors-in-retail
Correlation without Factors in Retail Cryptocurrency Markets
2412.04263
https://arxiv.org/abs/2412.04263v1
https://arxiv.org/pdf/2412.04263v1.pdf
https://github.com/Farmhouse121/Financial-Data-Science-in-Python/blob/main/Miscellaneous/Longer_Term_Crypto_Degrees_of_Freedom.ipynb
true
false
false
none
https://paperswithcode.com/paper/cofinal-enhancing-action-quality-assessment
CoFInAl: Enhancing Action Quality Assessment with Coarse-to-Fine Instruction Alignment
2404.13999
https://arxiv.org/abs/2404.13999v1
https://arxiv.org/pdf/2404.13999v1.pdf
https://github.com/zhoukanglei/cofinal_aqa
true
true
false
pytorch
https://paperswithcode.com/paper/vertical-structure-and-stability-of-accretion
Analysis of accretion disc structure and stability using open code for vertical structure
2303.02184
https://arxiv.org/abs/2303.02184v2
https://arxiv.org/pdf/2303.02184v2.pdf
https://github.com/andreytavleev/discverst
true
true
false
none
https://paperswithcode.com/paper/face-alignment-in-full-pose-range-a-3d-total
Face Alignment in Full Pose Range: A 3D Total Solution
1804.01005
http://arxiv.org/abs/1804.01005v1
http://arxiv.org/pdf/1804.01005v1.pdf
https://github.com/1996scarlet/dense-head-pose-estimation
false
false
true
tf
https://paperswithcode.com/paper/ulisse-a-tool-for-one-shot-sky-exploration
ULISSE: A Tool for One-shot Sky Exploration and its Application to Active Galactic Nuclei Detection
2208.10984
https://arxiv.org/abs/2208.10984v1
https://arxiv.org/pdf/2208.10984v1.pdf
https://github.com/larsdoorenbos/ulisse
true
true
true
none
https://paperswithcode.com/paper/variational-positive-incentive-noise-how
Variational Positive-incentive Noise: How Noise Benefits Models
2306.07651
https://arxiv.org/abs/2306.07651v1
https://arxiv.org/pdf/2306.07651v1.pdf
https://github.com/Panlizhi/VPN
false
false
true
none
https://paperswithcode.com/paper/efficient-sharpness-aware-minimization-for-2
Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models
2406.13137
https://arxiv.org/abs/2406.13137v1
https://arxiv.org/pdf/2406.13137v1.pdf
https://github.com/YL-wang/GraphSAM
true
true
false
pytorch
https://paperswithcode.com/paper/jaco-an-offline-running-privacy-aware-voice
Jaco: An Offline Running Privacy-aware Voice Assistant
2209.07775
https://arxiv.org/abs/2209.07775v1
https://arxiv.org/pdf/2209.07775v1.pdf
https://gitlab.com/Jaco-Assistant/Jaco-Master
true
false
true
none
https://paperswithcode.com/paper/finstreder-simple-and-fast-spoken-language
Finstreder: Simple and fast Spoken Language Understanding with Finite State Transducers using modern Speech-to-Text models
2206.14589
https://arxiv.org/abs/2206.14589v1
https://arxiv.org/pdf/2206.14589v1.pdf
https://gitlab.com/Jaco-Assistant/Jaco-Master
false
false
true
none
https://paperswithcode.com/paper/an-unsupervised-short-and-long-term-mask
An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly Detection
2208.09240
https://arxiv.org/abs/2208.09240v1
https://arxiv.org/pdf/2208.09240v1.pdf
https://github.com/qiumiao30/slmr
true
true
true
pytorch
https://paperswithcode.com/paper/a-closer-look-at-weakly-supervised-audio
A Closer Look at Weakly-Supervised Audio-Visual Source Localization
2209.09634
https://arxiv.org/abs/2209.09634v1
https://arxiv.org/pdf/2209.09634v1.pdf
https://github.com/stonemo/slavc
true
true
true
pytorch
https://paperswithcode.com/paper/modelling-wildland-fire-burn-severity-in
Modelling wildland fire burn severity in California using a spatial Super Learner approach
2311.16187
https://arxiv.org/abs/2311.16187v1
https://arxiv.org/pdf/2311.16187v1.pdf
https://github.com/Nicholas-Simafranca/Super_Learner_Wild_Fire
true
true
false
none
https://paperswithcode.com/paper/overstatement-net-equivalent-risk-limiting
Overstatement-Net-Equivalent Risk-Limiting Audit: ONEAudit
2303.03335
https://arxiv.org/abs/2303.03335v3
https://arxiv.org/pdf/2303.03335v3.pdf
https://github.com/pbstark/oneaudit
true
true
true
none
https://paperswithcode.com/paper/fcos3d-fully-convolutional-one-stage
FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detection
2104.10956
https://arxiv.org/abs/2104.10956v3
https://arxiv.org/pdf/2104.10956v3.pdf
https://github.com/vision-agh/pointpillars_backbone
false
false
true
pytorch
https://paperswithcode.com/paper/aicca-ai-driven-cloud-classification-atlas
AICCA: AI-driven Cloud Classification Atlas
2209.15096
https://arxiv.org/abs/2209.15096v3
https://arxiv.org/pdf/2209.15096v3.pdf
https://github.com/rdcep/clouds
true
true
false
tf
https://paperswithcode.com/paper/network-amplification-with-efficient-macs
Network Amplification With Efficient MACs Allocation
null
https://openaccess.thecvf.com/content/CVPR2022W/NAS/html/Liu_Network_Amplification_With_Efficient_MACs_Allocation_CVPRW_2022_paper.html
https://openaccess.thecvf.com/content/CVPR2022W/NAS/papers/Liu_Network_Amplification_With_Efficient_MACs_Allocation_CVPRW_2022_paper.pdf
https://github.com/0jason000/S-GhostNet
false
false
false
mindspore
https://paperswithcode.com/paper/masked-supervised-learning-for-semantic
Masked Supervised Learning for Semantic Segmentation
2210.00923
https://arxiv.org/abs/2210.00923v2
https://arxiv.org/pdf/2210.00923v2.pdf
https://github.com/hasibzunair/masksup-segmentation
true
true
true
pytorch
https://paperswithcode.com/paper/heterogeneous-graph-neural-network-for-2
Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation
2210.00538
https://arxiv.org/abs/2210.00538v2
https://arxiv.org/pdf/2210.00538v2.pdf
https://github.com/aixwinnie/hetedp
true
true
false
pytorch
https://paperswithcode.com/paper/react-a-review-comment-dataset-for
ReAct: A Review Comment Dataset for Actionability (and more)
2210.00443
https://arxiv.org/abs/2210.00443v1
https://arxiv.org/pdf/2210.00443v1.pdf
https://github.com/gtmdotme/react
true
true
false
none
https://paperswithcode.com/paper/learning-with-miselbo-the-mixture-cookbook
Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational Autoencoders
2209.15514
https://arxiv.org/abs/2209.15514v2
https://arxiv.org/pdf/2209.15514v2.pdf
https://github.com/lagergren-lab/mixturevaes
true
true
false
pytorch
https://paperswithcode.com/paper/relf-scalable-remote-live-forensics-for
ReLF: Scalable Remote Live Forensics for Android
null
https://ieeexplore.ieee.org/abstract/document/9724417
https://drive.google.com/file/u/0/d/1Jlq3shKDN_imbtibfw8wKQbP7rdjW1Ql/view
https://github.com/nexus-lab/relf-aosp-manifest
false
false
false
none
https://paperswithcode.com/paper/how-to-see-hidden-patterns-in-metamaterials
How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning
2111.05949
https://arxiv.org/abs/2111.05949v4
https://arxiv.org/pdf/2111.05949v4.pdf
https://github.com/zhichen96/interpretable_ml_metamaterials
true
true
true
pytorch
https://paperswithcode.com/paper/graph-neural-networks-can-recover-the-hidden
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure
2301.10956
https://arxiv.org/abs/2301.10956v4
https://arxiv.org/pdf/2301.10956v4.pdf
https://github.com/joisino/gnnrecover
true
true
true
pytorch
https://paperswithcode.com/paper/activation-based-sampling-for-pixel-to-image
Importance Sampling CAMs for Weakly-Supervised Segmentation
2203.12459
https://arxiv.org/abs/2203.12459v3
https://arxiv.org/pdf/2203.12459v3.pdf
https://github.com/arvijj/icam
true
true
true
pytorch
https://paperswithcode.com/paper/benchmarking-test-time-adaptation-against
Benchmarking Test-Time Adaptation against Distribution Shifts in Image Classification
2307.03133
https://arxiv.org/abs/2307.03133v1
https://arxiv.org/pdf/2307.03133v1.pdf
https://github.com/yuyongcan/benchmark-tta
true
true
true
pytorch
https://paperswithcode.com/paper/autonomous-driving-in-unstructured
Autonomous Driving in Unstructured Environments: How Far Have We Come?
2410.07701
https://arxiv.org/abs/2410.07701v3
https://arxiv.org/pdf/2410.07701v3.pdf
https://github.com/chaytonmin/survey-autonomous-driving-in-unstructured-environments
true
true
true
none
https://paperswithcode.com/paper/ghostnet-more-features-from-cheap-operations
GhostNet: More Features from Cheap Operations
1911.11907
https://arxiv.org/abs/1911.11907v2
https://arxiv.org/pdf/1911.11907v2.pdf
https://github.com/0jason000/S-GhostNet
false
false
true
mindspore
https://paperswithcode.com/paper/greedy-network-enlarging
Greedy Network Enlarging
2108.00177
https://arxiv.org/abs/2108.00177v3
https://arxiv.org/pdf/2108.00177v3.pdf
https://github.com/0jason000/S-GhostNet
false
false
true
mindspore
https://paperswithcode.com/paper/context-aware-3d-object-localization-from
Context-Aware 3D Object Localization from Single Calibrated Images: A Study of Basketballs
2309.03640
https://arxiv.org/abs/2309.03640v1
https://arxiv.org/pdf/2309.03640v1.pdf
https://github.com/gabriel-vanzandycke/deepsport
true
true
false
tf
https://paperswithcode.com/paper/exploring-the-enigma-of-neural-dynamics
Exploring the Enigma of Neural Dynamics Through A Scattering-Transform Mixer Landscape for Riemannian Manifold
2405.16357
https://arxiv.org/abs/2405.16357v1
https://arxiv.org/pdf/2405.16357v1.pdf
https://github.com/Dandy5721/ICML2024
true
true
false
pytorch
https://paperswithcode.com/paper/aerial-diffusion-text-guided-ground-to-aerial
Aerial Diffusion: Text Guided Ground-to-Aerial View Translation from a Single Image using Diffusion Models
2303.11444
https://arxiv.org/abs/2303.11444v2
https://arxiv.org/pdf/2303.11444v2.pdf
https://github.com/divyakraman/aerialdiffusion
true
true
true
pytorch
https://paperswithcode.com/paper/extending-the-wilds-benchmark-for-1
Extending the WILDS Benchmark for Unsupervised Adaptation
2112.05090
https://arxiv.org/abs/2112.05090v2
https://arxiv.org/pdf/2112.05090v2.pdf
https://github.com/huaxiuyao/c-mixup
false
false
true
pytorch
https://paperswithcode.com/paper/lostpaw-finding-lost-pets-using-a-contrastive
LostPaw: Finding Lost Pets using a Contrastive Learning-based Transformer with Visual Input
2304.14765
https://arxiv.org/abs/2304.14765v1
https://arxiv.org/pdf/2304.14765v1.pdf
https://github.com/vandrw/lostpaw-transformer
true
true
false
pytorch
https://paperswithcode.com/paper/bayesian-system-identification-for-structures
Bayesian system identification for structures considering spatial and temporal correlation
2305.00867
https://arxiv.org/abs/2305.00867v2
https://arxiv.org/pdf/2305.00867v2.pdf
https://github.com/JanKoune/bayesian_si_with_correlation
true
true
false
none
https://paperswithcode.com/paper/post-acquisition-image-based-compensation-for
Post-acquisition image based compensation for thickness variation in microscopy section series
1411.6970
http://arxiv.org/abs/1411.6970v2
http://arxiv.org/pdf/1411.6970v2.pdf
https://github.com/saalfeldlab/em-thickness-estimation
true
true
true
none
https://paperswithcode.com/paper/a-measurement-of-the-dark-energy-equation-of
Constraints on dark energy from TDCOSMO & SLACS lenses
2310.11977
https://arxiv.org/abs/2310.11977v2
https://arxiv.org/pdf/2310.11977v2.pdf
https://github.com/nataliehogg/slide
true
true
true
none
https://paperswithcode.com/paper/it-takes-two-learning-to-plan-for-human-robot
It Takes Two: Learning to Plan for Human-Robot Cooperative Carrying
2209.12890
https://arxiv.org/abs/2209.12890v2
https://arxiv.org/pdf/2209.12890v2.pdf
https://github.com/eleyng/cooperative_planner
true
false
true
pytorch
https://paperswithcode.com/paper/maximal-causes-for-exponential-family
Generic Unsupervised Optimization for a Latent Variable Model With Exponential Family Observables
2003.02214
https://arxiv.org/abs/2003.02214v3
https://arxiv.org/pdf/2003.02214v3.pdf
https://github.com/tvlearn/evo
true
true
false
pytorch
https://paperswithcode.com/paper/a-certified-radius-guided-attack-framework-to
A Certified Radius-Guided Attack Framework to Image Segmentation Models
2304.02693
https://arxiv.org/abs/2304.02693v1
https://arxiv.org/pdf/2304.02693v1.pdf
https://github.com/randomizedheap/cr_attack
true
true
false
pytorch
https://paperswithcode.com/paper/dds3d-dense-pseudo-labels-with-dynamic
DDS3D: Dense Pseudo-Labels with Dynamic Threshold for Semi-Supervised 3D Object Detection
2303.05079
https://arxiv.org/abs/2303.05079v2
https://arxiv.org/pdf/2303.05079v2.pdf
https://github.com/hust-jy/dds3d
true
true
true
pytorch
https://paperswithcode.com/paper/evaluating-parameter-efficient-transfer
Evaluating Parameter-Efficient Transfer Learning Approaches on SURE Benchmark for Speech Understanding
2303.03267
https://arxiv.org/abs/2303.03267v1
https://arxiv.org/pdf/2303.03267v1.pdf
https://github.com/declare-lab/speech-adapters
true
true
true
pytorch
https://paperswithcode.com/paper/analyzing-multi-task-learning-for-abstractive
Analyzing Multi-Task Learning for Abstractive Text Summarization
2210.14606
https://arxiv.org/abs/2210.14606v2
https://arxiv.org/pdf/2210.14606v2.pdf
https://github.com/fkirste/gem_emnlp2022-toasts
true
true
true
pytorch
https://paperswithcode.com/paper/improving-visual-semantic-embedding-with
Improving Visual-Semantic Embedding with Adaptive Pooling and Optimization Objective
2210.02206
https://arxiv.org/abs/2210.02206v1
https://arxiv.org/pdf/2210.02206v1.pdf
https://github.com/96-zachary/vse_2ad
true
true
false
pytorch
https://paperswithcode.com/paper/knowledge-distillation-from-cross-teaching
Knowledge Distillation from Cross Teaching Teachers for Efficient Semi-Supervised Abdominal Organ Segmentation in CT
2211.05942
https://arxiv.org/abs/2211.05942v1
https://arxiv.org/pdf/2211.05942v1.pdf
https://github.com/jwc-rad/mislight
true
true
true
pytorch
https://paperswithcode.com/paper/optimal-stopping-of-gauss-markov-bridges
Optimal stopping of Gauss-Markov bridges
2211.05835
https://arxiv.org/abs/2211.05835v4
https://arxiv.org/pdf/2211.05835v4.pdf
https://github.com/aguazz/osp_gmb
true
true
false
none
https://paperswithcode.com/paper/a-mountain-shaped-single-stage-network-for
A Mountain-Shaped Single-Stage Network for Accurate Image Restoration
2305.05146
https://arxiv.org/abs/2305.05146v1
https://arxiv.org/pdf/2305.05146v1.pdf
https://github.com/Tombs98/M3SNet
true
false
false
pytorch
https://paperswithcode.com/paper/chinese-sequence-labeling-with-semi
Chinese Sequence Labeling with Semi-Supervised Boundary-Aware Language Model Pre-training
2404.05560
https://arxiv.org/abs/2404.05560v1
https://arxiv.org/pdf/2404.05560v1.pdf
https://github.com/modelscope/adaseq
true
true
false
pytorch
https://paperswithcode.com/paper/deep-residual-learning-for-image-recognition
Deep Residual Learning for Image Recognition
1512.03385
http://arxiv.org/abs/1512.03385v1
http://arxiv.org/pdf/1512.03385v1.pdf
https://github.com/tanjeffreyz/deep-residual-learning
false
false
true
pytorch
https://paperswithcode.com/paper/think-on-process-dynamic-process-generation
Think-on-Process: Dynamic Process Generation for Collaborative Development of Multi-Agent System
2409.06568
https://arxiv.org/abs/2409.06568v1
https://arxiv.org/pdf/2409.06568v1.pdf
https://github.com/aizhouym/think-on-process
true
true
false
none
https://paperswithcode.com/paper/celebi-the-craft-effortless-localisation-and
CELEBI: The CRAFT Effortless Localisation and Enhanced Burst Inspection Pipeline
2301.13484
https://arxiv.org/abs/2301.13484v2
https://arxiv.org/pdf/2301.13484v2.pdf
https://github.com/askap-craco/celebi
true
true
true
none
https://paperswithcode.com/paper/adjoint-based-projections-for-uncertainty
Adjoint-Based Projections for Uncertainty Quantification near Stochastically Perturbed Limit Cycles and Tori
2404.13429
https://arxiv.org/abs/2404.13429v1
https://arxiv.org/pdf/2404.13429v1.pdf
https://github.com/hdankowicz/covariance-bvp2023-scripts
true
true
false
none
https://paperswithcode.com/paper/delving-deep-into-rectifiers-surpassing-human
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
1502.01852
http://arxiv.org/abs/1502.01852v1
http://arxiv.org/pdf/1502.01852v1.pdf
https://github.com/tanjeffreyz/deep-residual-learning
false
false
true
pytorch
https://paperswithcode.com/paper/a-machine-learning-photon-detection-algorithm
A machine learning photon detection algorithm for coherent X-ray ultrafast fluctuation analysis
2206.09064
https://arxiv.org/abs/2206.09064v1
https://arxiv.org/pdf/2206.09064v1.pdf
https://github.com/slaclab/ml_xpfs
true
false
false
tf
https://paperswithcode.com/paper/class-specific-explainability-for-deep-time
Class-Specific Explainability for Deep Time Series Classifiers
2210.05411
https://arxiv.org/abs/2210.05411v1
https://arxiv.org/pdf/2210.05411v1.pdf
https://github.com/rameshdoddaiah/demux
true
true
false
pytorch
https://paperswithcode.com/paper/null-hypothesis-test-for-anomaly-detection
Null Hypothesis Test for Anomaly Detection
2210.02226
https://arxiv.org/abs/2210.02226v3
https://arxiv.org/pdf/2210.02226v3.pdf
https://github.com/manuelszewc/null_hypothesis_test_for_anomaly_detection
true
true
true
pytorch
https://paperswithcode.com/paper/invariance-principle-meets-out-of
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs
2202.05441
https://arxiv.org/abs/2202.05441v3
https://arxiv.org/pdf/2202.05441v3.pdf
https://github.com/lfhase/ciga
true
true
true
pytorch
https://paperswithcode.com/paper/parameter-efficient-mixture-of-experts
Parameter-Efficient Mixture-of-Experts Architecture for Pre-trained Language Models
2203.01104
https://arxiv.org/abs/2203.01104v4
https://arxiv.org/pdf/2203.01104v4.pdf
https://github.com/rucaibox/mpoe
true
true
true
jax
https://paperswithcode.com/paper/nonparametric-monitoring-of-sunspot-number
Nonparametric monitoring of sunspot number observations: a case study
2106.13535
https://arxiv.org/abs/2106.13535v1
https://arxiv.org/pdf/2106.13535v1.pdf
https://github.com/sophiano/cusvm
false
false
true
none
https://paperswithcode.com/paper/nonparametric-robust-monitoring-of-time
Nonparametric robust monitoring of time series panel data
2010.11826
http://arxiv.org/abs/2010.11826v1
http://arxiv.org/pdf/2010.11826v1.pdf
https://github.com/sophiano/cusvm
false
false
true
none
https://paperswithcode.com/paper/neural-speech-synthesis-with-transformer
Neural Speech Synthesis with Transformer Network
1809.08895
http://arxiv.org/abs/1809.08895v3
http://arxiv.org/pdf/1809.08895v3.pdf
https://github.com/choiHkk/Transformer-TTS
false
false
true
pytorch
https://paperswithcode.com/paper/adversarial-feature-augmentation-for-cross
Adversarial Feature Augmentation for Cross-domain Few-shot Classification
2208.11021
https://arxiv.org/abs/2208.11021v1
https://arxiv.org/pdf/2208.11021v1.pdf
https://github.com/youthhoo/afa_for_few_shot_learning
true
true
true
pytorch
https://paperswithcode.com/paper/pmc-vqa-visual-instruction-tuning-for-medical
PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering
2305.10415
https://arxiv.org/abs/2305.10415v6
https://arxiv.org/pdf/2305.10415v6.pdf
https://github.com/xiaoman-zhang/PMC-VQA
true
true
true
pytorch
https://paperswithcode.com/paper/rubioroberta-a-pre-trained-biomedical
RuBioRoBERTa: a pre-trained biomedical language model for Russian language biomedical text mining
2204.03951
https://arxiv.org/abs/2204.03951v1
https://arxiv.org/pdf/2204.03951v1.pdf
https://github.com/pavel-blinov/RuMedBench
false
false
true
pytorch
https://paperswithcode.com/paper/evaluating-the-benefits-quantifying-the
Evaluating the Benefits: Quantifying the Effects of TCP Options, QUIC, and CDNs on Throughput
2309.10516
https://arxiv.org/abs/2309.10516v1
https://arxiv.org/pdf/2309.10516v1.pdf
https://github.com/tumi8/active-tcp-and-quic-measurements
true
true
false
none
https://paperswithcode.com/paper/natural-tts-synthesis-by-conditioning-wavenet
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
1712.05884
http://arxiv.org/abs/1712.05884v2
http://arxiv.org/pdf/1712.05884v2.pdf
https://github.com/choiHkk/Transformer-TTS
false
false
true
pytorch
https://paperswithcode.com/paper/vmformer-end-to-end-video-matting-with
VMFormer: End-to-End Video Matting with Transformer
2208.12801
https://arxiv.org/abs/2208.12801v2
https://arxiv.org/pdf/2208.12801v2.pdf
https://github.com/SHI-Labs/VMFormer
false
false
true
pytorch
https://paperswithcode.com/paper/generalizing-graph-neural-networks-beyond
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs
2006.11468
https://arxiv.org/abs/2006.11468v2
https://arxiv.org/pdf/2006.11468v2.pdf
https://github.com/GitEventhandler/H2GCN-PyTorch
false
false
true
pytorch
https://paperswithcode.com/paper/exploiting-reward-shifting-in-value-based
Optimistic Curiosity Exploration and Conservative Exploitation with Linear Reward Shaping
2209.07288
https://arxiv.org/abs/2209.07288v2
https://arxiv.org/pdf/2209.07288v2.pdf
https://github.com/holarissun/rewardshifting
true
true
false
pytorch
https://paperswithcode.com/paper/benchmarking-node-outlier-detection-on-graphs
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs
2206.10071
https://arxiv.org/abs/2206.10071v2
https://arxiv.org/pdf/2206.10071v2.pdf
https://github.com/pygod-team/pygod
true
true
true
pytorch
https://paperswithcode.com/paper/a-rigorous-study-of-the-deep-taylor
A Rigorous Study Of The Deep Taylor Decomposition
2211.08425
https://arxiv.org/abs/2211.08425v1
https://arxiv.org/pdf/2211.08425v1.pdf
https://github.com/berleon/a-rigorous-study-of-the-deep-taylor-decomposition
true
true
false
pytorch
https://paperswithcode.com/paper/a-light-cnn-for-deep-face-representation-with
A Light CNN for Deep Face Representation with Noisy Labels
1511.02683
http://arxiv.org/abs/1511.02683v4
http://arxiv.org/pdf/1511.02683v4.pdf
https://dagshub.com/Bharat-mtr/LightCNN
false
false
false
none
https://paperswithcode.com/paper/features-for-the-0-1-knapsack-problem-based
Features for the 0-1 knapsack problem based on inclusionwise maximal solutions
2211.09665
https://arxiv.org/abs/2211.09665v1
https://arxiv.org/pdf/2211.09665v1.pdf
https://github.com/jorikjooken/knapsackfeatures
true
true
false
none
https://paperswithcode.com/paper/conversational-fashion-image-retrieval-via
Conversational Fashion Image Retrieval via Multiturn Natural Language Feedback
2106.04128
https://arxiv.org/abs/2106.04128v1
https://arxiv.org/pdf/2106.04128v1.pdf
https://github.com/yyf775/MultiturnFashionRetrieval
true
false
true
none
https://paperswithcode.com/paper/ig-rl-inductive-graph-reinforcement-learning
IG-RL: Inductive Graph Reinforcement Learning for Massive-Scale Traffic Signal Control
2003.05738
https://arxiv.org/abs/2003.05738v6
https://arxiv.org/pdf/2003.05738v6.pdf
https://github.com/FXDevailly/IG-RL
true
true
true
pytorch
https://paperswithcode.com/paper/model-based-graph-reinforcement-learning-for
Model-based graph reinforcement learning for inductive traffic signal control
2208.00659
https://arxiv.org/abs/2208.00659v1
https://arxiv.org/pdf/2208.00659v1.pdf
https://github.com/FXDevailly/IG-RL
false
false
true
pytorch
https://paperswithcode.com/paper/constrained-cyclegan-for-effective-generation
Constrained CycleGAN for Effective Generation of Ultrasound Sector Images of Improved Spatial Resolution
2309.00995
https://arxiv.org/abs/2309.00995v1
https://arxiv.org/pdf/2309.00995v1.pdf
https://github.com/xfsun99/ccyclegan-tf2
true
true
false
tf
https://paperswithcode.com/paper/a-1
A
null
https://www.mdpi.com/1424-8220/22/21/8186/
https://www.mdpi.com/1424-8220/22/21/8186/pdf?version=1667184651
https://github.com/nexus-lab/iot-service-blockchain
false
false
false
none
https://paperswithcode.com/paper/phenomenological-modelling-of-the-crab-nebula
Phenomenological modelling of the Crab Nebula's broad band energy spectrum and its apparent extension
2203.11502
https://arxiv.org/abs/2203.11502v3
https://arxiv.org/pdf/2203.11502v3.pdf
https://github.com/dieterhorns/crab_pheno
true
true
false
none
https://paperswithcode.com/paper/pareto-invariant-risk-minimization
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization
2206.07766
https://arxiv.org/abs/2206.07766v2
https://arxiv.org/pdf/2206.07766v2.pdf
https://github.com/lfhase/ciga
false
false
true
pytorch
https://paperswithcode.com/paper/variational-graph-auto-encoders
Variational Graph Auto-Encoders
1611.07308
http://arxiv.org/abs/1611.07308v1
http://arxiv.org/pdf/1611.07308v1.pdf
https://github.com/lfhase/ciga
false
false
true
pytorch
https://paperswithcode.com/paper/secure-decentralized-iot-service-platform-1
Secure Decentralized IoT Service Platform
null
https://www.mdpi.com/1424-8220/22/21/8186/htm
https://www.mdpi.com/1424-8220/22/21/8186/pdf?version=
https://github.com/nexus-lab/iot-service-blockchain
false
false
false
none
https://paperswithcode.com/paper/secure-decentralized-iot-service-platform-2
Secure Decentralized IoT Service Platform Using Consortium
null
https://www.mdpi.com/1424-8220/22/21/8186/htm/
https://www.mdpi.com/1424-8220/22/21/8186/pdf/
https://github.com/nexus-lab/iot-service-blockchain
false
false
false
none
https://paperswithcode.com/paper/prompt-to-prompt-image-editing-with-cross
Prompt-to-Prompt Image Editing with Cross Attention Control
2208.01626
https://arxiv.org/abs/2208.01626v1
https://arxiv.org/pdf/2208.01626v1.pdf
https://github.com/bloc97/CrossAttentionControl
false
false
true
pytorch