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

Dataset card Data Studio Files
xet
Community
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https://paperswithcode.com/paper/benchmarking-chinese-text-recognition
Benchmarking Chinese Text Recognition: Datasets, Baselines, and an Empirical Study
2112.15093
https://arxiv.org/abs/2112.15093v2
https://arxiv.org/pdf/2112.15093v2.pdf
https://github.com/fudanvi/benchmarking-chinese-text-recognition
true
true
true
pytorch
https://paperswithcode.com/paper/fbnetgen-task-aware-gnn-based-fmri-analysis
FBNETGEN: Task-aware GNN-based fMRI Analysis via Functional Brain Network Generation
2205.12465
https://arxiv.org/abs/2205.12465v2
https://arxiv.org/pdf/2205.12465v2.pdf
https://github.com/wayfear/fbnetgen
true
true
false
pytorch
https://paperswithcode.com/paper/affect2mm-affective-analysis-of-multimedia
Affect2MM: Affective Analysis of Multimedia Content Using Emotion Causality
2103.06541
https://arxiv.org/abs/2103.06541v1
https://arxiv.org/pdf/2103.06541v1.pdf
https://github.com/mikecheninoulu/Emotional-gesture-papers
false
false
true
none
https://paperswithcode.com/paper/survey-on-emotional-body-gesture-recognition
Survey on Emotional Body Gesture Recognition
1801.07481
http://arxiv.org/abs/1801.07481v1
http://arxiv.org/pdf/1801.07481v1.pdf
https://github.com/mikecheninoulu/Emotional-gesture-papers
false
false
true
none
https://paperswithcode.com/paper/a-prototype-oriented-framework-for
A Prototype-Oriented Framework for Unsupervised Domain Adaptation
2110.12024
https://arxiv.org/abs/2110.12024v1
https://arxiv.org/pdf/2110.12024v1.pdf
https://github.com/korawat-tanwisuth/proto_da
true
true
false
pytorch
https://paperswithcode.com/paper/visually-dehallucinative-instruction-1
Visually Dehallucinative Instruction Generation: Know What You Don't Know
2402.09717
https://arxiv.org/abs/2402.09717v1
https://arxiv.org/pdf/2402.09717v1.pdf
https://github.com/ncsoft/idk
true
true
true
none
https://paperswithcode.com/paper/sub-instruction-aware-vision-and-language
Sub-Instruction Aware Vision-and-Language Navigation
2004.02707
https://arxiv.org/abs/2004.02707v2
https://arxiv.org/pdf/2004.02707v2.pdf
https://github.com/YicongHong/Fine-Grained-R2R
true
true
true
none
https://paperswithcode.com/paper/meta-learning-via-learned-loss
Meta-Learning via Learned Loss
1906.05374
https://arxiv.org/abs/1906.05374v4
https://arxiv.org/pdf/1906.05374v4.pdf
https://github.com/facebookresearch/higher
false
false
true
pytorch
https://paperswithcode.com/paper/global-convergence-and-induced-kernels-of
Global Convergence and Generalization Bound of Gradient-Based Meta-Learning with Deep Neural Nets
2006.14606
https://arxiv.org/abs/2006.14606v2
https://arxiv.org/pdf/2006.14606v2.pdf
https://github.com/facebookresearch/higher
true
true
true
pytorch
https://paperswithcode.com/paper/meta-learning-symmetries-by
Meta-Learning Symmetries by Reparameterization
2007.02933
https://arxiv.org/abs/2007.02933v3
https://arxiv.org/pdf/2007.02933v3.pdf
https://github.com/facebookresearch/higher
false
false
true
pytorch
https://paperswithcode.com/paper/fat-deepffm-field-attentive-deep-field-aware
FAT-DeepFFM: Field Attentive Deep Field-aware Factorization Machine
1905.06336
https://arxiv.org/abs/1905.06336v1
https://arxiv.org/pdf/1905.06336v1.pdf
https://github.com/mindspore-ai/models/tree/master/research/recommend/Fat-DeepFFM
false
false
false
mindspore
https://paperswithcode.com/paper/statistically-unbiased-prediction-enables
Statistically unbiased prediction enables accurate denoising of voltage imaging data
null
https://www.biorxiv.org/content/10.1101/2022.11.17.516709v1.abstract
https://www.biorxiv.org/content/10.1101/2022.11.17.516709v1.full.pdf
https://github.com/NICALab/SUPPORT
true
false
false
pytorch
https://paperswithcode.com/paper/pinto-faithful-language-reasoning-using
PINTO: Faithful Language Reasoning Using Prompt-Generated Rationales
2211.01562
https://arxiv.org/abs/2211.01562v3
https://arxiv.org/pdf/2211.01562v3.pdf
https://github.com/wangpf3/pinto-faithful-language-reasoning
true
true
true
pytorch
https://paperswithcode.com/paper/unsupervised-selective-rationalization-with
Unsupervised Selective Rationalization with Noise Injection
2305.17534
https://arxiv.org/abs/2305.17534v1
https://arxiv.org/pdf/2305.17534v1.pdf
https://github.com/adamstorek/noise_injection
true
true
false
pytorch
https://paperswithcode.com/paper/you-only-look-once-unified-real-time-object
You Only Look Once: Unified, Real-Time Object Detection
1506.02640
http://arxiv.org/abs/1506.02640v5
http://arxiv.org/pdf/1506.02640v5.pdf
https://github.com/Kartik-Aggarwal/Real-Time-Traffic-Sign-Detection
false
false
true
pytorch
https://paperswithcode.com/paper/or-gym-a-reinforcement-learning-library-for
OR-Gym: A Reinforcement Learning Library for Operations Research Problems
2008.06319
https://arxiv.org/abs/2008.06319v2
https://arxiv.org/pdf/2008.06319v2.pdf
https://github.com/ashwin-M-D/DM-Gym
false
false
true
none
https://paperswithcode.com/paper/caching-in-networks-without-regret
LeadCache: Regret-Optimal Caching in Networks
2009.08228
https://arxiv.org/abs/2009.08228v4
https://arxiv.org/pdf/2009.08228v4.pdf
https://github.com/abhishekmitiitm/leadcache-neurips21
true
true
false
none
https://paperswithcode.com/paper/yolov4-optimal-speed-and-accuracy-of-object
YOLOv4: Optimal Speed and Accuracy of Object Detection
2004.10934
https://arxiv.org/abs/2004.10934v1
https://arxiv.org/pdf/2004.10934v1.pdf
https://github.com/david8862/keras-YOLOv3-model-set
false
false
true
tf
https://paperswithcode.com/paper/data-engineering-for-scaling-language-models
Data Engineering for Scaling Language Models to 128K Context
2402.10171
https://arxiv.org/abs/2402.10171v1
https://arxiv.org/pdf/2402.10171v1.pdf
https://github.com/franxyao/long-context-data-engineering
true
true
true
pytorch
https://paperswithcode.com/paper/implicit-sparse-regularization-the-impact-of
Implicit Sparse Regularization: The Impact of Depth and Early Stopping
2108.05574
https://arxiv.org/abs/2108.05574v2
https://arxiv.org/pdf/2108.05574v2.pdf
https://github.com/jiangyuan2li/implicit-sparse-regularization
true
true
true
pytorch
https://paperswithcode.com/paper/discourse-aware-unsupervised-summarization
Discourse-Aware Unsupervised Summarization for Long Scientific Documents
null
https://aclanthology.org/2021.eacl-main.93
https://aclanthology.org/2021.eacl-main.93.pdf
https://github.com/mirandrom/HipoRank
true
true
false
none
https://paperswithcode.com/paper/crowd-counting-on-images-with-scale-variation
Crowd Counting on Images with Scale Variation and Isolated Clusters
1909.03839
https://arxiv.org/abs/1909.03839v1
https://arxiv.org/pdf/1909.03839v1.pdf
https://github.com/HaoyueBaiZJU/SACANet-VisDrone-Crowd
false
false
false
pytorch
https://paperswithcode.com/paper/multi-agent-variational-occlusion-inference
Multi-Agent Variational Occlusion Inference Using People as Sensors
2109.02173
https://arxiv.org/abs/2109.02173v3
https://arxiv.org/pdf/2109.02173v3.pdf
https://github.com/sisl/MultiAgentVariationalOcclusionInference
true
true
true
pytorch
https://paperswithcode.com/paper/neural-discrete-representation-learning
Neural Discrete Representation Learning
1711.00937
http://arxiv.org/abs/1711.00937v2
http://arxiv.org/pdf/1711.00937v2.pdf
https://github.com/sisl/MultiAgentVariationalOcclusionInference
false
false
true
pytorch
https://paperswithcode.com/paper/adam-a-method-for-stochastic-optimization
Adam: A Method for Stochastic Optimization
1412.6980
http://arxiv.org/abs/1412.6980v9
http://arxiv.org/pdf/1412.6980v9.pdf
https://github.com/sisl/MultiAgentVariationalOcclusionInference
false
false
true
pytorch
https://paperswithcode.com/paper/leveraging-locality-in-abstractive-text
Leveraging Locality in Abstractive Text Summarization
2205.12476
https://arxiv.org/abs/2205.12476v2
https://arxiv.org/pdf/2205.12476v2.pdf
https://github.com/yixinl7/pagesum
true
true
true
pytorch
https://paperswithcode.com/paper/reflection-from-a-multi-species-material-and
Reflection from a multi-species material and its transmitted effective wavenumber
1712.05427
http://arxiv.org/abs/1712.05427v3
http://arxiv.org/pdf/1712.05427v3.pdf
https://github.com/arturgower/EffectiveWaves.jl
true
true
true
none
https://paperswithcode.com/paper/intermediate-layers-matter-in-momentum
Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning
2110.14805
https://arxiv.org/abs/2110.14805v1
https://arxiv.org/pdf/2110.14805v1.pdf
https://github.com/aakashrkaku/intermdiate_layer_matter_ssl
true
true
false
pytorch
https://paperswithcode.com/paper/bag-of-tricks-and-a-strong-baseline-for-image
Bag of Tricks and A Strong baseline for Image Copy Detection
2111.08004
https://arxiv.org/abs/2111.08004v2
https://arxiv.org/pdf/2111.08004v2.pdf
https://github.com/wangwenhao0716/isc-track2-submission
true
true
false
pytorch
https://paperswithcode.com/paper/domain-decomposition-for-entropy-regularized
Domain decomposition for entropy regularized optimal transport
2001.10986
https://arxiv.org/abs/2001.10986v2
https://arxiv.org/pdf/2001.10986v2.pdf
https://github.com/ismedina/DomDecOT.jl
false
false
true
none
https://paperswithcode.com/paper/computational-performance-of-deep
Computational Performance of Deep Reinforcement Learning to find Nash Equilibria
2104.12895
https://arxiv.org/abs/2104.12895v1
https://arxiv.org/pdf/2104.12895v1.pdf
https://github.com/ckrk/bidding_learning
true
true
true
pytorch
https://paperswithcode.com/paper/multimodal-knowledge-expansion
Multimodal Knowledge Expansion
2103.14431
https://arxiv.org/abs/2103.14431v3
https://arxiv.org/pdf/2103.14431v3.pdf
https://github.com/zihuixue/mke
true
true
true
none
https://paperswithcode.com/paper/accelerating-the-super-resolution
Accelerating the Super-Resolution Convolutional Neural Network
1608.00367
http://arxiv.org/abs/1608.00367v1
http://arxiv.org/pdf/1608.00367v1.pdf
https://github.com/MohammedAlkhrashi/TMA
false
false
true
none
https://paperswithcode.com/paper/learning-soccer-juggling-skills-with-layer
Learning Soccer Juggling Skills with Layer-wise Mixture-of-Experts
null
https://dl.acm.org/doi/10.1145/3528233.3530735
https://www.cs.ubc.ca/~van/papers/2022-SIGGRAPH-juggle/soccer_juggling.pdf
https://github.com/ZhaomingXie/soccer_juggle_release
false
true
false
pytorch
https://paperswithcode.com/paper/time-series-forecasting-with-llms
Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities
2402.10835
https://arxiv.org/abs/2402.10835v5
https://arxiv.org/pdf/2402.10835v5.pdf
https://github.com/mingyuj666/time-series-forecasting-with-llms
true
true
false
jax
https://paperswithcode.com/paper/proton-probing-schema-linking-information
Proton: Probing Schema Linking Information from Pre-trained Language Models for Text-to-SQL Parsing
2206.14017
https://arxiv.org/abs/2206.14017v2
https://arxiv.org/pdf/2206.14017v2.pdf
https://github.com/AlibabaResearch/DAMO-ConvAI/tree/main/proton
true
false
false
pytorch
https://paperswithcode.com/paper/person-transfer-gan-to-bridge-domain-gap-for
Person Transfer GAN to Bridge Domain Gap for Person Re-Identification
1711.08565
http://arxiv.org/abs/1711.08565v2
http://arxiv.org/pdf/1711.08565v2.pdf
https://github.com/ucas-vg/groupsampling
false
false
true
pytorch
https://paperswithcode.com/paper/on-monte-carlo-tree-search-for-weighted
On Monte Carlo Tree Search for Weighted Vertex Coloring
2202.01665
https://arxiv.org/abs/2202.01665v2
https://arxiv.org/pdf/2202.01665v2.pdf
https://github.com/cyril-grelier/gc_wvcp_mcts
true
true
true
none
https://paperswithcode.com/paper/a-theory-of-continuous-generative-flow
A theory of continuous generative flow networks
2301.12594
https://arxiv.org/abs/2301.12594v2
https://arxiv.org/pdf/2301.12594v2.pdf
https://github.com/saleml/continuous-gfn
true
true
false
pytorch
https://paperswithcode.com/paper/nlatool-an-application-for-enhanced-deep-text
NLATool: an Application for Enhanced Deep Text Understanding
null
https://aclanthology.org/C18-2026
https://aclanthology.org/C18-2026.pdf
https://github.com/interactionlab/nlatool
true
true
false
none
https://paperswithcode.com/paper/sub-word-information-in-pre-trained
Sub-word information in pre-trained biomedical word representations: evaluation and hyper-parameter optimization
null
https://aclanthology.org/W18-2307
https://aclanthology.org/W18-2307.pdf
https://github.com/dterg/bionlp-embed
true
true
false
none
https://paperswithcode.com/paper/deep-polarization-reconstruction-with-pdavis
Deep Polarization Reconstruction With PDAVIS Events
null
http://openaccess.thecvf.com//content/CVPR2023/html/Mei_Deep_Polarization_Reconstruction_With_PDAVIS_Events_CVPR_2023_paper.html
http://openaccess.thecvf.com//content/CVPR2023/papers/Mei_Deep_Polarization_Reconstruction_With_PDAVIS_Events_CVPR_2023_paper.pdf
https://github.com/sensorsini/e2p
true
true
false
pytorch
https://paperswithcode.com/paper/a-perturbation-based-out-of-sample-extension
A Perturbation-Based Kernel Approximation Framework
2009.02955
https://arxiv.org/abs/2009.02955v2
https://arxiv.org/pdf/2009.02955v2.pdf
https://github.com/roymitz/perturbation_out_of_sample_extension
true
true
true
none
https://paperswithcode.com/paper/unbiased-risk-estimation-in-the-normal-means
Unbiased Risk Estimation in the Normal Means Problem via Coupled Bootstrap Techniques
2111.09447
https://arxiv.org/abs/2111.09447v3
https://arxiv.org/pdf/2111.09447v3.pdf
https://github.com/nloliveira/coupled-bootstrap-risk-estimation
true
true
false
none
https://paperswithcode.com/paper/intrinsic-dimensionality-estimation-within
Intrinsic Dimensionality Estimation within Tight Localities: A Theoretical and Experimental Analysis
2209.14475
https://arxiv.org/abs/2209.14475v1
https://arxiv.org/pdf/2209.14475v1.pdf
https://github.com/radacha/tle
true
true
false
none
https://paperswithcode.com/paper/real-time-classification-geolocation-and
Real-time Classification, Geolocation and Interactive Visualization of COVID-19 Information Shared on Social Media to Better Understand Global Developments
null
https://aclanthology.org/2020.nlpcovid19-2.37
https://aclanthology.org/2020.nlpcovid19-2.37.pdf
https://github.com/mirandrom/crisistweetmap
true
true
false
pytorch
https://paperswithcode.com/paper/dialogstitch-synthetic-deeper-and-multi
DialogStitch: Synthetic Deeper and Multi-Context Task-Oriented Dialogs
null
https://aclanthology.org/2021.sigdial-1.3
https://aclanthology.org/2021.sigdial-1.3.pdf
https://github.com/facebookresearch/dialogstitch
true
true
false
none
https://paperswithcode.com/paper/effective-approaches-to-attention-based
Effective Approaches to Attention-based Neural Machine Translation
1508.04025
http://arxiv.org/abs/1508.04025v5
http://arxiv.org/pdf/1508.04025v5.pdf
https://github.com/bplank/teaching-dl4nlp
false
false
true
none
https://paperswithcode.com/paper/deep-contextualized-word-representations
Deep contextualized word representations
1802.05365
http://arxiv.org/abs/1802.05365v2
http://arxiv.org/pdf/1802.05365v2.pdf
https://github.com/bplank/teaching-dl4nlp
false
false
true
none
https://paperswithcode.com/paper/simcse-simple-contrastive-learning-of
SimCSE: Simple Contrastive Learning of Sentence Embeddings
2104.08821
https://arxiv.org/abs/2104.08821v4
https://arxiv.org/pdf/2104.08821v4.pdf
https://github.com/shuxinyin/SimCSE-Pytorch
false
false
true
pytorch
https://paperswithcode.com/paper/panoptic-segformer
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers
2109.03814
https://arxiv.org/abs/2109.03814v4
https://arxiv.org/pdf/2109.03814v4.pdf
https://github.com/zhiqi-li/Panoptic-SegFormer
true
true
true
pytorch
https://paperswithcode.com/paper/memory-efficient-meta-learning-with-large
Memory Efficient Meta-Learning with Large Images
2107.01105
https://arxiv.org/abs/2107.01105v2
https://arxiv.org/pdf/2107.01105v2.pdf
https://github.com/cambridge-mlg/LITE
true
true
true
pytorch
https://paperswithcode.com/paper/reduced-operator-inference-for-nonlinear
Reduced operator inference for nonlinear partial differential equations
2102.00083
https://arxiv.org/abs/2102.00083v2
https://arxiv.org/pdf/2102.00083v2.pdf
https://github.com/elizqian/operator-inference
true
true
true
none
https://paperswithcode.com/paper/learning-to-compose-with-professional
Learning to Compose with Professional Photographs on the Web
1702.00503
http://arxiv.org/abs/1702.00503v2
http://arxiv.org/pdf/1702.00503v2.pdf
https://github.com/yiling-chen/view-finding-network
true
true
true
tf
https://paperswithcode.com/paper/lift-learn-physics-informed-machine-learning
Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems
1912.08177
https://arxiv.org/abs/1912.08177v5
https://arxiv.org/pdf/1912.08177v5.pdf
https://github.com/elizqian/operator-inference
false
false
true
none
https://paperswithcode.com/paper/ucc-uncertainty-guided-cross-head-co-training
UCC: Uncertainty guided Cross-head Co-training for Semi-Supervised Semantic Segmentation
2205.10334
https://arxiv.org/abs/2205.10334v2
https://arxiv.org/pdf/2205.10334v2.pdf
https://github.com/voldemortX/DST-CBC
true
false
false
pytorch
https://paperswithcode.com/paper/towards-gradient-based-bilevel-optimization
Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond
2110.00455
https://arxiv.org/abs/2110.00455v2
https://arxiv.org/pdf/2110.00455v2.pdf
https://github.com/vis-opt-group/iaptt-gm
true
true
true
pytorch
https://paperswithcode.com/paper/adam-a-method-for-stochastic-optimization
Adam: A Method for Stochastic Optimization
1412.6980
http://arxiv.org/abs/1412.6980v9
http://arxiv.org/pdf/1412.6980v9.pdf
https://github.com/mirzaevinom/data_science_bowl_2018
false
false
true
tf
https://paperswithcode.com/paper/mask-r-cnn
Mask R-CNN
1703.06870
http://arxiv.org/abs/1703.06870v3
http://arxiv.org/pdf/1703.06870v3.pdf
https://github.com/mirzaevinom/data_science_bowl_2018
false
false
true
tf
https://paperswithcode.com/paper/learning-prototype-representations-across-few
Learning Prototype Representations Across Few-Shot Tasks for Event Detection
null
https://aclanthology.org/2021.emnlp-main.427
https://aclanthology.org/2021.emnlp-main.427.pdf
https://github.com/laiviet/fsl-proact
true
true
false
pytorch
https://paperswithcode.com/paper/generative-planning-for-temporally-1
Generative Planning for Temporally Coordinated Exploration in Reinforcement Learning
2201.09765
https://arxiv.org/abs/2201.09765v2
https://arxiv.org/pdf/2201.09765v2.pdf
https://github.com/Haichao-Zhang/generative-planning
true
false
false
pytorch
https://paperswithcode.com/paper/metric-learning-cross-entropy-vs-pairwise
A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses
2003.08983
https://arxiv.org/abs/2003.08983v3
https://arxiv.org/pdf/2003.08983v3.pdf
https://github.com/jeromerony/dml_cross_entropy
true
true
false
pytorch
https://paperswithcode.com/paper/fully-convolutional-siamese-neural-networks
Fully convolutional Siamese neural networks for buildings damage assessment from satellite images
2111.00508
https://arxiv.org/abs/2111.00508v1
https://arxiv.org/pdf/2111.00508v1.pdf
https://github.com/bloodaxe/xview2-solution
true
true
true
pytorch
https://paperswithcode.com/paper/progressive-growing-of-gans-for-improved
Progressive Growing of GANs for Improved Quality, Stability, and Variation
1710.10196
http://arxiv.org/abs/1710.10196v3
http://arxiv.org/pdf/1710.10196v3.pdf
https://github.com/valentingol/GANJax
false
false
true
jax
https://paperswithcode.com/paper/cross-domain-cross-architecture-black-box
Cross-domain Cross-architecture Black-box Attacks on Fine-tuned Models with Transferred Evolutionary Strategies
2208.13182
https://arxiv.org/abs/2208.13182v1
https://arxiv.org/pdf/2208.13182v1.pdf
https://github.com/hkust-knowcomp/tes
true
true
false
pytorch
https://paperswithcode.com/paper/visual-reasoning-strategies-for-effect-size
Visual Reasoning Strategies for Effect Size Judgments and Decisions
2007.14516
https://arxiv.org/abs/2007.14516v3
https://arxiv.org/pdf/2007.14516v3.pdf
https://github.com/fredhohman/awesome-mathematical-notation-design
false
false
true
none
https://paperswithcode.com/paper/sciencemeter-tracking-scientific-knowledge
ScienceMeter: Tracking Scientific Knowledge Updates in Language Models
2505.24302
https://arxiv.org/abs/2505.24302v1
https://arxiv.org/pdf/2505.24302v1.pdf
https://github.com/yikee/sciencemeter
true
true
true
pytorch
https://paperswithcode.com/paper/fast-3d-registration-with-accurate
Fast 3D registration with accurate optimisation and little learning for Learn2Reg 2021
2112.03053
https://arxiv.org/abs/2112.03053v1
https://arxiv.org/pdf/2112.03053v1.pdf
https://github.com/multimodallearning/convexadam
true
true
false
pytorch
https://paperswithcode.com/paper/melgan-generative-adversarial-networks-for
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
1910.06711
https://arxiv.org/abs/1910.06711v3
https://arxiv.org/pdf/1910.06711v3.pdf
https://github.com/jaywalnut310/melgan-pytorch
false
false
true
pytorch
https://paperswithcode.com/paper/mcmi-multi-cycle-image-translation-with
MCMI: Multi-Cycle Image Translation with Mutual Information Constraints
2007.02919
https://arxiv.org/abs/2007.02919v1
https://arxiv.org/pdf/2007.02919v1.pdf
https://github.com/yuzhenmao/MI_P2V
false
false
true
pytorch
https://paperswithcode.com/paper/pix2vox-multi-scale-context-aware-3d-object
Pix2Vox++: Multi-scale Context-aware 3D Object Reconstruction from Single and Multiple Images
2006.12250
https://arxiv.org/abs/2006.12250v2
https://arxiv.org/pdf/2006.12250v2.pdf
https://github.com/yuzhenmao/MI_P2V
false
false
true
pytorch
https://paperswithcode.com/paper/a-unified-view-on-graph-neural-networks-as-1
A Unified View on Graph Neural Networks as Graph Signal Denoising
2010.01777
https://arxiv.org/abs/2010.01777v2
https://arxiv.org/pdf/2010.01777v2.pdf
https://github.com/alge24/ADA-UGNN
true
true
true
pytorch
https://paperswithcode.com/paper/systematic-analysis-of-programming-languages
Systematic Analysis of Programming Languages and Their Execution Environments for Spectre Attacks
2111.12528
https://arxiv.org/abs/2111.12528v1
https://arxiv.org/pdf/2111.12528v1.pdf
https://github.com/misc0110/pteditor
false
false
true
none
https://paperswithcode.com/paper/merger-rate-density-of-binary-black-holes-1
Merger rate density of binary black holes through isolated Population I, II, III and extremely metal-poor binary star evolution
2110.10846
https://arxiv.org/abs/2110.10846v4
https://arxiv.org/pdf/2110.10846v4.pdf
https://github.com/atrtnkw/bseemp
true
true
false
none
https://paperswithcode.com/paper/physics-based-model-to-predict-the-acoustic
Physics-based model to predict the acoustic detection distance of terrestrial autonomous recording units over the diel cycle and across seasons: insights from an Alpine and a Neotropical forest
2211.16077
https://arxiv.org/abs/2211.16077v1
https://arxiv.org/pdf/2211.16077v1.pdf
https://github.com/shaupert/haupert_mee_2022
true
true
false
none
https://paperswithcode.com/paper/multidimensional-representations-in-late-life
Multidimensional representations in late-life depression: convergence in neuroimaging, cognition, clinical symptomatology and genetics
2110.11347
https://arxiv.org/abs/2110.11347v2
https://arxiv.org/pdf/2110.11347v2.pdf
https://github.com/anbai106/mlni
false
false
true
pytorch
https://paperswithcode.com/paper/reproducible-evaluation-of-diffusion-mri
Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimers disease
1812.11183
https://arxiv.org/abs/1812.11183v4
https://arxiv.org/pdf/1812.11183v4.pdf
https://github.com/anbai106/mlni
false
false
true
pytorch
https://paperswithcode.com/paper/are-transformers-more-robust-than-cnns
Are Transformers More Robust Than CNNs?
2111.05464
https://arxiv.org/abs/2111.05464v1
https://arxiv.org/pdf/2111.05464v1.pdf
https://github.com/ytongbai/ViTs-vs-CNNs
true
true
true
pytorch
https://paperswithcode.com/paper/controlled-text-generation-as-continuous
Controlled Text Generation as Continuous Optimization with Multiple Constraints
2108.01850
https://arxiv.org/abs/2108.01850v1
https://arxiv.org/pdf/2108.01850v1.pdf
https://github.com/sachin19/mucoco
false
false
true
pytorch
https://paperswithcode.com/paper/texttt-express-extensible-high-level
$\texttt{express}$: extensible, high-level workflows for swifter $\textit{ab initio}$ materials modeling
2109.11724
https://arxiv.org/abs/2109.11724v1
https://arxiv.org/pdf/2109.11724v1.pdf
https://github.com/MineralsCloud/Express.jl
true
true
true
none
https://paperswithcode.com/paper/let-each-quantum-bit-choose-its-basis-gates
Let Each Quantum Bit Choose Its Basis Gates
2208.13380
https://arxiv.org/abs/2208.13380v2
https://arxiv.org/pdf/2208.13380v2.pdf
https://github.com/sophlin/nonstandard_2qbasis_gates
true
true
false
none
https://paperswithcode.com/paper/issafe-improving-semantic-segmentation-in
ISSAFE: Improving Semantic Segmentation in Accidents by Fusing Event-based Data
2008.08974
https://arxiv.org/abs/2008.08974v2
https://arxiv.org/pdf/2008.08974v2.pdf
https://github.com/jamycheung/ISSAFE
true
true
true
pytorch
https://paperswithcode.com/paper/exploring-event-driven-dynamic-context-for
Exploring Event-driven Dynamic Context for Accident Scene Segmentation
2112.05006
https://arxiv.org/abs/2112.05006v1
https://arxiv.org/pdf/2112.05006v1.pdf
https://github.com/jamycheung/ISSAFE
true
true
true
pytorch
https://paperswithcode.com/paper/antipodal-robotic-grasping-using-generative
Antipodal Robotic Grasping using Generative Residual Convolutional Neural Network
1909.04810
https://arxiv.org/abs/1909.04810v4
https://arxiv.org/pdf/1909.04810v4.pdf
https://github.com/SteveHao74/shahao_GR-ConvNet
false
false
true
pytorch
https://paperswithcode.com/paper/physics-guided-deep-learning-for-data
Utilising physics-guided deep learning to overcome data scarcity
2211.15664
https://arxiv.org/abs/2211.15664v3
https://arxiv.org/pdf/2211.15664v3.pdf
https://github.com/jinshuaibai/pgdl_review
true
true
true
tf
https://paperswithcode.com/paper/yake-keyword-extraction-from-single-documents
YAKE! Keyword extraction from single documents using multiple local features
null
https://repositorio.inesctec.pt/server/api/core/bitstreams/ef121a01-a0a6-4be8-945d-3324a58fc944/content
https://repositorio.inesctec.pt/server/api/core/bitstreams/ef121a01-a0a6-4be8-945d-3324a58fc944/content
https://github.com/LIAAD/yake
false
false
false
tf
https://paperswithcode.com/paper/denoising-of-3d-mr-images-using-a-voxel-wise
Denoising of 3D MR images using a voxel-wise hybrid residual MLP-CNN model to improve small lesion diagnostic confidence
2209.13818
https://arxiv.org/abs/2209.13818v1
https://arxiv.org/pdf/2209.13818v1.pdf
https://github.com/laowangbobo/residual_mlp_cnn_mixer
true
true
true
pytorch
https://paperswithcode.com/paper/detect-consolidate-delineate-scalable-mapping
Detect, consolidate, delineate: scalable mapping of field boundaries using satellite images
null
https://www.mdpi.com/2072-4292/13/11/2197
https://www.mdpi.com/2072-4292/13/11/2197/pdf
https://github.com/waldnerf/decode
false
true
false
mxnet
https://paperswithcode.com/paper/size-limits-sensitivity-in-all-kinetic
Size limits sensitivity in all kinetic schemes
2112.07777
https://arxiv.org/abs/2112.07777v1
https://arxiv.org/pdf/2112.07777v1.pdf
https://github.com/jaowen/nested-hysteresis
true
true
true
none
https://paperswithcode.com/paper/generalization-bounds-for-meta-learning-an
Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis
2109.14595
https://arxiv.org/abs/2109.14595v2
https://arxiv.org/pdf/2109.14595v2.pdf
https://github.com/livreq/meta-sgld
true
true
false
pytorch
https://paperswithcode.com/paper/optab-public-code-for-generating-gas-opacity
Optab: Public code for generating gas opacity tables for radiation hydrodynamics simulations
2112.05689
https://arxiv.org/abs/2112.05689v1
https://arxiv.org/pdf/2112.05689v1.pdf
https://github.com/nombac/optab
true
true
true
none
https://paperswithcode.com/paper/automatically-learning-compact-quality-aware
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems
2006.10815
https://arxiv.org/abs/2006.10815v2
https://arxiv.org/pdf/2006.10815v2.pdf
https://github.com/PredOptwithSoftConstraint/PredOptwithSoftConstraint
false
false
true
pytorch
https://paperswithcode.com/paper/an-imaging-search-for-post-main-sequence
An Imaging Search for Post-Main-Sequence Planets of Sirius B
2112.05234
https://arxiv.org/abs/2112.05234v1
https://arxiv.org/pdf/2112.05234v1.pdf
https://github.com/mileslucas/sirius-b
true
true
true
none
https://paperswithcode.com/paper/online-mixed-integer-optimization-in
Online Mixed-Integer Optimization in Milliseconds
1907.02206
https://arxiv.org/abs/1907.02206v4
https://arxiv.org/pdf/1907.02206v4.pdf
https://github.com/bstellato/mlopt
true
true
true
pytorch
https://paperswithcode.com/paper/learning-mixed-integer-convex-optimization
Learning Mixed-Integer Convex Optimization Strategies for Robot Planning and Control
2004.03736
https://arxiv.org/abs/2004.03736v2
https://arxiv.org/pdf/2004.03736v2.pdf
https://github.com/bstellato/mlopt
false
false
true
pytorch
https://paperswithcode.com/paper/a-twin-decoder-structure-for-incompressible
A twin-decoder structure for incompressible laminar flow reconstruction with uncertainty estimation around 2D obstacles
2104.03619
https://arxiv.org/abs/2104.03619v2
https://arxiv.org/pdf/2104.03619v2.pdf
https://github.com/jviquerat/twin_autoencoder
true
true
true
tf
https://paperswithcode.com/paper/a-deep-knowledge-distillation-framework-for
A Deep Knowledge Distillation framework for EEG assisted enhancement of single-lead ECG based sleep staging
2112.07252
https://arxiv.org/abs/2112.07252v2
https://arxiv.org/pdf/2112.07252v2.pdf
https://github.com/acrophase/sleep_staging_kd
true
true
false
pytorch
https://paperswithcode.com/paper/efficient-convnet-for-real-time-semantic
Efficient ConvNet for Real-time Semantic Segmentation
null
https://ieeexplore.ieee.org/document/7995966
https://ieeexplore.ieee.org/document/7995966
https://github.com/yangyucheng000/erfnet
false
false
false
mindspore
https://paperswithcode.com/paper/u-time-a-fully-convolutional-network-for-time
U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging
1910.11162
https://arxiv.org/abs/1910.11162v1
https://arxiv.org/pdf/1910.11162v1.pdf
https://github.com/acrophase/sleep_staging_kd
false
false
true
pytorch
https://paperswithcode.com/paper/product1m-towards-weakly-supervised-instance
Product1M: Towards Weakly Supervised Instance-Level Product Retrieval via Cross-modal Pretraining
2107.14572
https://arxiv.org/abs/2107.14572v2
https://arxiv.org/pdf/2107.14572v2.pdf
https://github.com/zhanxlin/product1m
true
true
true
pytorch