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

Dataset card Data Studio Files
xet
Community
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https://paperswithcode.com/paper/recommendations-for-item-set-completion-on
Recommendations for Item Set Completion: On the Semantics of Item Co-Occurrence With Data Sparsity, Input Size, and Input Modalities
2105.04376
https://arxiv.org/abs/2105.04376v1
https://arxiv.org/pdf/2105.04376v1.pdf
https://github.com/lgalke/aae-recommender
true
true
false
pytorch
https://paperswithcode.com/paper/active-fire-detection-in-landsat-8-imagery-a
Active Fire Detection in Landsat-8 Imagery: a Large-Scale Dataset and a Deep-Learning Study
2101.03409
https://arxiv.org/abs/2101.03409v2
https://arxiv.org/pdf/2101.03409v2.pdf
https://github.com/pereira-gha/activefire
true
true
true
tf
https://paperswithcode.com/paper/gift-learning-transformation-invariant-dense-1
GIFT: Learning Transformation-Invariant Dense Visual Descriptors via Group CNNs
1911.05932
https://arxiv.org/abs/1911.05932v1
https://arxiv.org/pdf/1911.05932v1.pdf
https://github.com/zju3dv/GIFT
false
false
true
pytorch
https://paperswithcode.com/paper/trtr-visual-tracking-with-transformer
TrTr: Visual Tracking with Transformer
2105.03817
https://arxiv.org/abs/2105.03817v1
https://arxiv.org/pdf/2105.03817v1.pdf
https://github.com/tongtybj/TrTr
true
true
false
pytorch
https://paperswithcode.com/paper/copula-based-normalizing-flows
Copula-Based Normalizing Flows
2107.07352
https://arxiv.org/abs/2107.07352v1
https://arxiv.org/pdf/2107.07352v1.pdf
https://github.com/MikeLasz/Copula-Based-Normalizing-Flows
true
true
false
pytorch
https://paperswithcode.com/paper/maximum-likelihood-minimum-effort
Maximum Likelihood, Minimum Effort
1106.5458
https://arxiv.org/abs/1106.5458v2
https://arxiv.org/pdf/1106.5458v2.pdf
https://github.com/fbm2718/QREM
false
false
true
none
https://paperswithcode.com/paper/quantum-overlapping-tomography
Quantum Overlapping Tomography
1908.02754
https://arxiv.org/abs/1908.02754v2
https://arxiv.org/pdf/1908.02754v2.pdf
https://github.com/fbm2718/QREM
false
false
true
none
https://paperswithcode.com/paper/assortativity-in-cognition
Assortativity in cognition
2205.15114
https://arxiv.org/abs/2205.15114v1
https://arxiv.org/pdf/2205.15114v1.pdf
https://github.com/eugeniovicario/assortativity_in_cognition
true
true
false
none
https://paperswithcode.com/paper/training-time-friendly-network-for-real-time
Training-Time-Friendly Network for Real-Time Object Detection
1909.00700
https://arxiv.org/abs/1909.00700v3
https://arxiv.org/pdf/1909.00700v3.pdf
https://github.com/ximilar-com/xcenternet
false
false
true
tf
https://paperswithcode.com/paper/objects-as-points
Objects as Points
1904.07850
http://arxiv.org/abs/1904.07850v2
http://arxiv.org/pdf/1904.07850v2.pdf
https://github.com/ximilar-com/xcenternet
false
false
true
tf
https://paperswithcode.com/paper/deformable-convolutional-networks
Deformable Convolutional Networks
1703.06211
http://arxiv.org/abs/1703.06211v3
http://arxiv.org/pdf/1703.06211v3.pdf
https://github.com/ximilar-com/xcenternet
false
false
true
tf
https://paperswithcode.com/paper/barbershop-gan-based-image-compositing-using
Barbershop: GAN-based Image Compositing using Segmentation Masks
2106.01505
https://arxiv.org/abs/2106.01505v2
https://arxiv.org/pdf/2106.01505v2.pdf
https://github.com/ZPdesu/Barbershop
false
false
true
pytorch
https://paperswithcode.com/paper/knowledge-distillation-from-bert-transformer
Knowledge Distillation from BERT Transformer to Speech Transformer for Intent Classification
2108.02598
https://arxiv.org/abs/2108.02598v1
https://arxiv.org/pdf/2108.02598v1.pdf
https://github.com/Jiang-Yidi/TransformerDistillation-SLU
true
true
false
pytorch
https://paperswithcode.com/paper/doremi-first-glance-at-a-universal-omr
DoReMi: First glance at a universal OMR dataset
2107.07786
https://arxiv.org/abs/2107.07786v1
https://arxiv.org/pdf/2107.07786v1.pdf
https://github.com/apacha/OMR-Datasets
false
false
true
none
https://paperswithcode.com/paper/flex-unifying-evaluation-for-few-shot-nlp
FLEX: Unifying Evaluation for Few-Shot NLP
2107.07170
https://arxiv.org/abs/2107.07170v2
https://arxiv.org/pdf/2107.07170v2.pdf
https://github.com/allenai/unifew
true
true
true
pytorch
https://paperswithcode.com/paper/few-shot-forecasting-of-time-series-with
Few-Shot Forecasting of Time-Series with Heterogeneous Channels
2204.03456
https://arxiv.org/abs/2204.03456v2
https://arxiv.org/pdf/2204.03456v2.pdf
https://github.com/radrumond/timehetnet
true
true
true
tf
https://paperswithcode.com/paper/speeding-up-bigclam-implementation-on-snap
Speeding Up BigClam Implementation on SNAP
1712.01209
https://arxiv.org/abs/1712.01209v2
https://arxiv.org/pdf/1712.01209v2.pdf
https://github.com/liuchbryan/snap/tree/master/contrib/ICL-bigclam_speedup
true
false
false
none
https://paperswithcode.com/paper/question-generation-for-adaptive-education
Question Generation for Adaptive Education
2106.04262
https://arxiv.org/abs/2106.04262v1
https://arxiv.org/pdf/2106.04262v1.pdf
https://github.com/meghabyte/acl2021-education
true
true
false
pytorch
https://paperswithcode.com/paper/reconfigurable-intelligent-surfaces-a-signal
Reconfigurable Intelligent Surfaces: A Signal Processing Perspective With Wireless Applications
2102.00742
https://arxiv.org/abs/2102.00742v2
https://arxiv.org/pdf/2102.00742v2.pdf
https://github.com/emilbjornson/SP_Cup_2021
false
false
true
none
https://paperswithcode.com/paper/efficient-bitruss-decomposition-for-large
Efficient Bitruss Decomposition for Large-scale Bipartite Graphs
2001.06111
http://arxiv.org/abs/2001.06111v1
http://arxiv.org/pdf/2001.06111v1.pdf
https://github.com/kartiklakhotia/RECEIPT
false
false
true
none
https://paperswithcode.com/paper/scan-flood-fillscaff-an-efficient-automatic
Scan-flood Fill(SCAFF): an Efficient Automatic Precise Region Filling Algorithm for Complicated Regions
1906.03366
https://arxiv.org/abs/1906.03366v1
https://arxiv.org/pdf/1906.03366v1.pdf
https://github.com/SherylHYX/Scan-flood-Fill
true
true
true
none
https://paperswithcode.com/paper/revisiting-contrastive-methods-for
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations
2106.05967
https://arxiv.org/abs/2106.05967v3
https://arxiv.org/pdf/2106.05967v3.pdf
https://github.com/wvangansbeke/Revisiting-Contrastive-SSL
true
true
true
pytorch
https://paperswithcode.com/paper/learning-manifold-patch-based-representations-1
Learning Manifold Patch-Based Representations of Man-Made Shapes
1906.12337
https://arxiv.org/abs/1906.12337v3
https://arxiv.org/pdf/1906.12337v3.pdf
https://github.com/dmsm/LearningPatches
true
false
false
pytorch
https://paperswithcode.com/paper/modeling-and-control-of-morphing-covers-for
Modeling and Control of Morphing Covers for the Adaptive Morphology of Humanoid Robots
2207.01025
https://arxiv.org/abs/2207.01025v2
https://arxiv.org/pdf/2207.01025v2.pdf
https://github.com/ami-iit/mystica
true
true
false
none
https://paperswithcode.com/paper/yolact-real-time-instance-segmentation
YOLACT: Real-time Instance Segmentation
1904.02689
https://arxiv.org/abs/1904.02689v2
https://arxiv.org/pdf/1904.02689v2.pdf
https://github.com/Abhijeet8901/Instance-Segmentation-using-YOLACT
false
false
true
pytorch
https://paperswithcode.com/paper/computing-multiple-solutions-of-topology
Computing multiple solutions of topology optimization problems
2004.11797
https://arxiv.org/abs/2004.11797v2
https://arxiv.org/pdf/2004.11797v2.pdf
https://bitbucket.org/papadopoulos/deflatedbarrier
true
true
false
none
https://paperswithcode.com/paper/deep-learning-models-for-multilingual-hate
Deep Learning Models for Multilingual Hate Speech Detection
2004.06465
https://arxiv.org/abs/2004.06465v3
https://arxiv.org/pdf/2004.06465v3.pdf
https://github.com/hate-alert/DE-LIMIT
false
false
true
pytorch
https://paperswithcode.com/paper/you-only-look-yourself-unsupervised-and
You Only Look Yourself: Unsupervised and Untrained Single Image Dehazing Neural Network
2006.16829
https://arxiv.org/abs/2006.16829v1
https://arxiv.org/pdf/2006.16829v1.pdf
https://github.com/XLearning-SCU/2021-IJCV-YOLY
true
false
false
pytorch
https://paperswithcode.com/paper/hvsrweb-an-open-source-web-based-application
HVSRweb: An Open-Source, Web-Based Application for Horizontal-to-Vertical Spectral Ratio Processing
2106.06050
https://arxiv.org/abs/2106.06050v1
https://arxiv.org/pdf/2106.06050v1.pdf
https://github.com/jpvantassel/hvsrweb
true
true
false
none
https://paperswithcode.com/paper/an-inexact-augmented-lagrangian-method-for
An inexact augmented Lagrangian method for nonsmooth optimization on Riemannian manifold
1911.09900
http://arxiv.org/abs/1911.09900v2
http://arxiv.org/pdf/1911.09900v2.pdf
https://github.com/KKDeng/mialm_code_share
true
false
true
none
https://paperswithcode.com/paper/benchmarks-for-deep-off-policy-evaluation-1
Benchmarks for Deep Off-Policy Evaluation
2103.16596
https://arxiv.org/abs/2103.16596v1
https://arxiv.org/pdf/2103.16596v1.pdf
https://github.com/tedmoskovitz/TOP
false
false
true
pytorch
https://paperswithcode.com/paper/structured-attention-for-unsupervised
Structured Attention for Unsupervised Dialogue Structure Induction
2009.08552
https://arxiv.org/abs/2009.08552v2
https://arxiv.org/pdf/2009.08552v2.pdf
https://github.com/Liang-Qiu/SVRNN-dialogues
true
true
true
pytorch
https://paperswithcode.com/paper/cascade-cost-volume-for-high-resolution-multi
Cascade Cost Volume for High-Resolution Multi-View Stereo and Stereo Matching
1912.06378
https://arxiv.org/abs/1912.06378v3
https://arxiv.org/pdf/1912.06378v3.pdf
https://github.com/apchenstu/mvsnerf
false
false
true
pytorch
https://paperswithcode.com/paper/structure-extraction-in-task-oriented
Structure Extraction in Task-Oriented Dialogues with Slot Clustering
2203.00073
https://arxiv.org/abs/2203.00073v3
https://arxiv.org/pdf/2203.00073v3.pdf
https://github.com/Liang-Qiu/SVRNN-dialogues
false
false
true
pytorch
https://paperswithcode.com/paper/invariance-principle-meets-information
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization
2106.06607
https://arxiv.org/abs/2106.06607v2
https://arxiv.org/pdf/2106.06607v2.pdf
https://github.com/ahujak/IB-IRM
true
true
false
pytorch
https://paperswithcode.com/paper/defending-against-backdoors-in-federated
Defending against Backdoors in Federated Learning with Robust Learning Rate
2007.03767
https://arxiv.org/abs/2007.03767v4
https://arxiv.org/pdf/2007.03767v4.pdf
https://github.com/TinfoilHat0/Defending-Against-Backdoors-with-Robust-Learning-Rate
true
true
true
pytorch
https://paperswithcode.com/paper/mimicking-production-behavior-with-generated
Mimicking Production Behavior with Generated Mocks
2208.01321
https://arxiv.org/abs/2208.01321v4
https://arxiv.org/pdf/2208.01321v4.pdf
https://github.com/castor-software/rick-experiments
true
true
false
none
https://paperswithcode.com/paper/structext-structured-text-understanding-with
StrucTexT: Structured Text Understanding with Multi-Modal Transformers
2108.02923
https://arxiv.org/abs/2108.02923v3
https://arxiv.org/pdf/2108.02923v3.pdf
https://github.com/PaddlePaddle/VIMER/tree/main/StrucTexT
true
false
false
paddle
https://paperswithcode.com/paper/pair-diffusion-a-comprehensive-multimodal
PAIR Diffusion: A Comprehensive Multimodal Object-Level Image Editor
null
http://openaccess.thecvf.com//content/CVPR2024/html/Goel_PAIR_Diffusion_A_Comprehensive_Multimodal_Object-Level_Image_Editor_CVPR_2024_paper.html
http://openaccess.thecvf.com//content/CVPR2024/papers/Goel_PAIR_Diffusion_A_Comprehensive_Multimodal_Object-Level_Image_Editor_CVPR_2024_paper.pdf
https://github.com/picsart-ai-research/pair-diffusion
true
true
false
pytorch
https://paperswithcode.com/paper/faster-ltn-a-neuro-symbolic-end-to-end-object
Faster-LTN: a neuro-symbolic, end-to-end object detection architecture
2107.01877
https://arxiv.org/abs/2107.01877v1
https://arxiv.org/pdf/2107.01877v1.pdf
https://gitlab.com/grains2/Faster-LTN
true
true
false
tf
https://paperswithcode.com/paper/optimizing-graphical-procedures-for
Optimizing Graphical Procedures for Multiplicity Control in a Confirmatory Clinical Trial via Deep Learning
1908.10262
https://arxiv.org/abs/1908.10262v2
https://arxiv.org/pdf/1908.10262v2.pdf
https://github.com/tian-yu-zhan/dnn_optimization
true
true
false
none
https://paperswithcode.com/paper/a-large-scale-study-on-research-code-quality
A large-scale study on research code quality and execution
2103.12793
https://arxiv.org/abs/2103.12793v1
https://arxiv.org/pdf/2103.12793v1.pdf
https://github.com/atrisovic/dataverse-r-study
true
true
true
none
https://paperswithcode.com/paper/fine-grained-continual-learning
Rehearsal-Free Continual Learning over Small Non-I.I.D. Batches
1907.03799
https://arxiv.org/abs/1907.03799v3
https://arxiv.org/pdf/1907.03799v3.pdf
https://github.com/vlomonaco/core50
false
false
true
none
https://paperswithcode.com/paper/hdr-environment-map-estimation-for-real-time
HDR Environment Map Estimation for Real-Time Augmented Reality
2011.10687
https://arxiv.org/abs/2011.10687v5
https://arxiv.org/pdf/2011.10687v5.pdf
https://github.com/apple/ml-envmapnet
true
false
true
none
https://paperswithcode.com/paper/potential-gap-using-reactive-policies-to
Potential Gap: Using Reactive Policies to Guarantee Safe Navigation
2103.11491
https://arxiv.org/abs/2103.11491v1
https://arxiv.org/pdf/2103.11491v1.pdf
https://github.com/ivaROS/PotentialGap
false
false
true
none
https://paperswithcode.com/paper/wkb-based-scheme-with-adaptive-step-size
WKB-based scheme with adaptive step size control for the Schrödinger equation in the highly oscillatory regime
2102.03107
https://arxiv.org/abs/2102.03107v2
https://arxiv.org/pdf/2102.03107v2.pdf
https://github.com/JannisKoerner/adaptive-WKB-marching-method
true
true
true
none
https://paperswithcode.com/paper/frustum-pointnets-for-3d-object-detection
Frustum PointNets for 3D Object Detection from RGB-D Data
1711.08488
http://arxiv.org/abs/1711.08488v2
http://arxiv.org/pdf/1711.08488v2.pdf
https://github.com/charlesq34/frustum-pointnets
true
false
true
tf
https://paperswithcode.com/paper/trajformer-trajectory-prediction-with-local
Trajformer: Trajectory Prediction with Local Self-Attentive Contexts for Autonomous Driving
2011.14910
https://arxiv.org/abs/2011.14910v1
https://arxiv.org/pdf/2011.14910v1.pdf
https://github.com/Manojbhat09/Trajformer
true
true
true
pytorch
https://paperswithcode.com/paper/transition-based-bubble-parsing-improvements
Transition-based Bubble Parsing: Improvements on Coordination Structure Prediction
2107.06905
https://arxiv.org/abs/2107.06905v1
https://arxiv.org/pdf/2107.06905v1.pdf
https://github.com/tzshi/bubble-parser-acl21
true
true
false
pytorch
https://paperswithcode.com/paper/terapipe-token-level-pipeline-parallelism-for
TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models
2102.07988
https://arxiv.org/abs/2102.07988v2
https://arxiv.org/pdf/2102.07988v2.pdf
https://github.com/zhuohan123/terapipe
true
true
false
pytorch
https://paperswithcode.com/paper/global-context-enhanced-social-recommendation
Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks
2110.04039
https://arxiv.org/abs/2110.04039v1
https://arxiv.org/pdf/2110.04039v1.pdf
https://github.com/xhcdream/sr-hgnn
true
true
false
pytorch
https://paperswithcode.com/paper/recommendations-for-datasets-for-source-code
Recommendations for Datasets for Source Code Summarization
1904.02660
http://arxiv.org/abs/1904.02660v1
http://arxiv.org/pdf/1904.02660v1.pdf
https://github.com/sjj0403/Datasets-for-code-summarization-evaluation
false
false
true
pytorch
https://paperswithcode.com/paper/star-sparse-transformer-based-action
STAR: Sparse Transformer-based Action Recognition
2107.07089
https://arxiv.org/abs/2107.07089v1
https://arxiv.org/pdf/2107.07089v1.pdf
https://github.com/imj2185/STAR
true
false
true
pytorch
https://paperswithcode.com/paper/word-recognition-with-deep-conditional-random
Word Recognition with Deep Conditional Random Fields
1612.01072
http://arxiv.org/abs/1612.01072v1
http://arxiv.org/pdf/1612.01072v1.pdf
https://github.com/ganggit/deepCRFs
true
true
false
none
https://paperswithcode.com/paper/towards-end-to-end-semi-supervised-learning
Towards End-to-end Semi-supervised Learning for One-stage Object Detection
2302.11299
https://arxiv.org/abs/2302.11299v1
https://arxiv.org/pdf/2302.11299v1.pdf
https://github.com/luogen1996/oneteacher
true
true
false
pytorch
https://paperswithcode.com/paper/addressing-function-approximation-error-in
Addressing Function Approximation Error in Actor-Critic Methods
1802.09477
http://arxiv.org/abs/1802.09477v3
http://arxiv.org/pdf/1802.09477v3.pdf
https://github.com/pkasala/ContinuesControl
false
false
true
pytorch
https://paperswithcode.com/paper/machine-learning-kondo-physics-using
Machine learning of Kondo physics using variational autoencoders and symbolic regression
2107.08013
https://arxiv.org/abs/2107.08013v2
https://arxiv.org/pdf/2107.08013v2.pdf
https://github.com/ColeMiles/SpectralVAE
true
true
false
pytorch
https://paperswithcode.com/paper/ms-mda-multisource-marginal-distribution
MS-MDA: Multisource Marginal Distribution Adaptation for Cross-subject and Cross-session EEG Emotion Recognition
2107.07740
https://arxiv.org/abs/2107.07740v1
https://arxiv.org/pdf/2107.07740v1.pdf
https://github.com/VoiceBeer/MS-MDA
true
true
false
pytorch
https://paperswithcode.com/paper/approaches-to-constrained-quantum-approximate
Approaches to Constrained Quantum Approximate Optimization
2010.06660
https://arxiv.org/abs/2010.06660v3
https://arxiv.org/pdf/2010.06660v3.pdf
https://github.com/Quantum-Software-Tools/dqva-and-circuit-cutting
false
false
true
none
https://paperswithcode.com/paper/latentkeypointgan-controlling-gans-via-latent
LatentKeypointGAN: Controlling Images via Latent Keypoints
2103.15812
https://arxiv.org/abs/2103.15812v5
https://arxiv.org/pdf/2103.15812v5.pdf
https://github.com/DELTA37/LatentKeypointGAN
false
false
false
pytorch
https://paperswithcode.com/paper/r-drop-regularized-dropout-for-neural
R-Drop: Regularized Dropout for Neural Networks
2106.14448
https://arxiv.org/abs/2106.14448v2
https://arxiv.org/pdf/2106.14448v2.pdf
https://github.com/zbp-xxxp/R-Drop-Paddle
false
false
false
paddle
https://paperswithcode.com/paper/generalized-variational-inference-in-function
Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning
2205.06342
https://arxiv.org/abs/2205.06342v2
https://arxiv.org/pdf/2205.06342v2.pdf
https://github.com/MrHuff/GWI
true
true
false
pytorch
https://paperswithcode.com/paper/autoscore-survival-developing-interpretable
AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data
2106.06957
https://arxiv.org/abs/2106.06957v1
https://arxiv.org/pdf/2106.06957v1.pdf
https://github.com/nliulab/AutoScore-Survival
true
true
true
none
https://paperswithcode.com/paper/atspy-automated-time-series-forecasting-in
AtsPy: Automated Time Series Forecasting in Python
null
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3580631
https://poseidon01.ssrn.com/delivery.php?ID=707091125114113026107095123106012077118020024084061089000004119106020064002075106096026057102032006102108123122117114083097012038034045078021105097124103065089098001069030017007065001016083087005002028016069112115112083121104114122001107118013017105025&EXT=pdf&INDEX=TRUE
https://github.com/firmai/atspy
false
false
false
tf
https://paperswithcode.com/paper/explanations-based-on-the-missing-towards
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives
1802.07623
http://arxiv.org/abs/1802.07623v2
http://arxiv.org/pdf/1802.07623v2.pdf
https://github.com/IBM/Contrastive-Explanation-Method
true
true
true
tf
https://paperswithcode.com/paper/scalability-in-perception-for-autonomous
Scalability in Perception for Autonomous Driving: Waymo Open Dataset
1912.04838
https://arxiv.org/abs/1912.04838v7
https://arxiv.org/pdf/1912.04838v7.pdf
https://github.com/p-mc-grath/DMMFODS
false
false
true
pytorch
https://paperswithcode.com/paper/u-net-convolutional-networks-for-biomedical
U-Net: Convolutional Networks for Biomedical Image Segmentation
1505.04597
http://arxiv.org/abs/1505.04597v1
http://arxiv.org/pdf/1505.04597v1.pdf
https://github.com/p-mc-grath/DMMFODS
false
false
true
pytorch
https://paperswithcode.com/paper/densely-connected-convolutional-networks
Densely Connected Convolutional Networks
1608.06993
http://arxiv.org/abs/1608.06993v5
http://arxiv.org/pdf/1608.06993v5.pdf
https://github.com/p-mc-grath/DMMFODS
false
false
true
pytorch
https://paperswithcode.com/paper/lale-consistent-automated-machine-learning
Lale: Consistent Automated Machine Learning
2007.01977
https://arxiv.org/abs/2007.01977v1
https://arxiv.org/pdf/2007.01977v1.pdf
https://github.com/IBM/Lale.jl
false
false
true
none
https://paperswithcode.com/paper/iranis-a-large-scale-dataset-of-farsi-license
Iranis: A Large-scale Dataset of Farsi License Plate Characters
2101.00295
https://arxiv.org/abs/2101.00295v1
https://arxiv.org/pdf/2101.00295v1.pdf
https://github.com/alitourani/Iranis-dataset
true
false
true
none
https://paperswithcode.com/paper/modeling-natural-language-emergence-with
Modeling natural language emergence with integral transform theory and reinforcement learning
1812.01431
http://arxiv.org/abs/1812.01431v1
http://arxiv.org/pdf/1812.01431v1.pdf
https://github.com/Quiltomics/NLERL
true
true
false
tf
https://paperswithcode.com/paper/accurate-liability-estimation-improves-power
Accurate Liability Estimation Improves Power in Ascertained Case Control Studies
1409.2448
http://arxiv.org/abs/1409.2448v3
http://arxiv.org/pdf/1409.2448v3.pdf
https://github.com/omerwe/LEAP
true
true
false
none
https://paperswithcode.com/paper/bag-tag-em-a-new-dutch-stemmer
Bag \& Tag'em - A New Dutch Stemmer
null
https://aclanthology.org/2020.lrec-1.477
https://aclanthology.org/2020.lrec-1.477.pdf
https://github.com/Anne-Jonker/Bag-Tag-em
true
true
false
none
https://paperswithcode.com/paper/guided-search-for-desired-functional
Guided search for desired functional responses via Bayesian optimization of generative model: hysteresis loop shape engineering in ferroelectrics
2004.12512
https://arxiv.org/abs/2004.12512v1
https://arxiv.org/pdf/2004.12512v1.pdf
https://github.com/ramav87/Ferrosim
true
true
false
none
https://paperswithcode.com/paper/to-vr-or-not-to-vr-is-virtual-reality
To VR or not to VR: Is virtual reality suitable to understand software development metrics?
2109.13768
https://arxiv.org/abs/2109.13768v1
https://arxiv.org/pdf/2109.13768v1.pdf
https://gitlab.com/babiaxr/aframe-babia-components
true
true
false
none
https://paperswithcode.com/paper/image-based-correction-of-continuous-and
Image-Based Correction of Continuous and Discontinuous Non-Planar Axial Distortion in Serial Section Microscopy
1511.01161
http://arxiv.org/abs/1511.01161v2
http://arxiv.org/pdf/1511.01161v2.pdf
https://github.com/saalfeldlab/em-thickness-estimation
true
true
false
none
https://paperswithcode.com/paper/spatial-temporal-transformer-for-dynamic
Spatial-Temporal Transformer for Dynamic Scene Graph Generation
2107.12309
https://arxiv.org/abs/2107.12309v2
https://arxiv.org/pdf/2107.12309v2.pdf
https://github.com/yrcong/sttran
true
true
true
pytorch
https://paperswithcode.com/paper/yolox-exceeding-yolo-series-in-2021
YOLOX: Exceeding YOLO Series in 2021
2107.08430
https://arxiv.org/abs/2107.08430v2
https://arxiv.org/pdf/2107.08430v2.pdf
https://github.com/StephenStorm/YOLOX
false
false
true
pytorch
https://paperswithcode.com/paper/probing-for-labeled-dependency-trees
Probing for Labeled Dependency Trees
2203.12971
https://arxiv.org/abs/2203.12971v1
https://arxiv.org/pdf/2203.12971v1.pdf
https://github.com/personads/depprobe
true
false
false
pytorch
https://paperswithcode.com/paper/dropgnn-random-dropouts-increase-the
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks
2111.06283
https://arxiv.org/abs/2111.06283v1
https://arxiv.org/pdf/2111.06283v1.pdf
https://github.com/karolismart/dropgnn
true
true
true
pytorch
https://paperswithcode.com/paper/automatic-annotation-and-evaluation-of-error
Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction
null
https://aclanthology.org/P17-1074
https://aclanthology.org/P17-1074.pdf
https://github.com/chrisjbryant/errant
true
true
false
none
https://paperswithcode.com/paper/epidemic-thresholds-of-infectious-diseases-on
Epidemic Thresholds of Infectious Diseases on Tie-Decay Networks
2009.12932
https://arxiv.org/abs/2009.12932v2
https://arxiv.org/pdf/2009.12932v2.pdf
https://github.com/qinyichen/tie-decay-epidemic-threshold
true
true
true
none
https://paperswithcode.com/paper/opinionated-practices-for-teaching
Opinionated practices for teaching reproducibility: motivation, guided instruction and practice
2109.13656
https://arxiv.org/abs/2109.13656v2
https://arxiv.org/pdf/2109.13656v2.pdf
https://github.com/UBC-MDS/opinionated-practices-for-teaching-reproducibility
true
false
false
none
https://paperswithcode.com/paper/parallel-peeling-of-bipartite-networks-for
Parallel Peeling of Bipartite Networks for Hierarchical Dense Subgraph Discovery
2110.12511
https://arxiv.org/abs/2110.12511v1
https://arxiv.org/pdf/2110.12511v1.pdf
https://github.com/kartiklakhotia/RECEIPT
true
true
false
none
https://paperswithcode.com/paper/pseudo-relevance-feedback-for-multiple
Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval
2106.11251
https://arxiv.org/abs/2106.11251v2
https://arxiv.org/pdf/2106.11251v2.pdf
https://github.com/cmacdonald/pyterrier_colbert
true
false
true
pytorch
https://paperswithcode.com/paper/implicit-svd-for-graph-representation
Implicit SVD for Graph Representation Learning
2111.06312
https://arxiv.org/abs/2111.06312v1
https://arxiv.org/pdf/2111.06312v1.pdf
https://github.com/samihaija/isvd
true
true
false
tf
https://paperswithcode.com/paper/a-consolidated-open-knowledge-representation
A Consolidated Open Knowledge Representation for Multiple Texts
null
https://aclanthology.org/W17-0902
https://aclanthology.org/W17-0902.pdf
https://github.com/vered1986/OKR
true
true
false
none
https://paperswithcode.com/paper/massformer-tandem-mass-spectrum-prediction
MassFormer: Tandem Mass Spectrum Prediction for Small Molecules using Graph Transformers
2111.04824
https://arxiv.org/abs/2111.04824v3
https://arxiv.org/pdf/2111.04824v3.pdf
https://github.com/samgoldman97/ms-pred
false
false
true
pytorch
https://paperswithcode.com/paper/automatically-polyconvex-strain-energy
Data-driven Tissue Mechanics with Polyconvex Neural Ordinary Differential Equations
2110.03774
https://arxiv.org/abs/2110.03774v2
https://arxiv.org/pdf/2110.03774v2.pdf
https://github.com/tajtac/node
true
true
false
jax
https://paperswithcode.com/paper/scalable-visual-transformers-with
Scalable Vision Transformers with Hierarchical Pooling
2103.10619
https://arxiv.org/abs/2103.10619v2
https://arxiv.org/pdf/2103.10619v2.pdf
https://github.com/MonashAI/HVT
true
true
true
pytorch
https://paperswithcode.com/paper/window-level-is-a-strong-denoising-surrogate
Window-Level is a Strong Denoising Surrogate
2105.07153
https://arxiv.org/abs/2105.07153v1
https://arxiv.org/pdf/2105.07153v1.pdf
https://github.com/zubaerimran/SSWL-IDN
true
true
true
pytorch
https://paperswithcode.com/paper/galactic-diffuse-gamma-rays-meet-the-pev
Galactic diffuse gamma rays meet the PeV frontier
2203.15759
https://arxiv.org/abs/2203.15759v3
https://arxiv.org/pdf/2203.15759v3.pdf
https://github.com/tospines/gamma-variable_high-resolution
true
true
false
none
https://paperswithcode.com/paper/nifty-web-apps-build-a-web-app-for-any-text
Nifty Web Apps: Build a Web App for Any Text-Based Programming Assignment
2010.04671
https://arxiv.org/abs/2010.04671v1
https://arxiv.org/pdf/2010.04671v1.pdf
https://github.com/kevinlin1/nifty-web-apps
true
false
true
none
https://paperswithcode.com/paper/not-just-a-black-box-learning-important
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences
1605.01713
http://arxiv.org/abs/1605.01713v3
http://arxiv.org/pdf/1605.01713v3.pdf
https://github.com/pytorch/captum
false
false
true
pytorch
https://paperswithcode.com/paper/vit-cx-causal-explanation-of-vision
ViT-CX: Causal Explanation of Vision Transformers
2211.03064
https://arxiv.org/abs/2211.03064v3
https://arxiv.org/pdf/2211.03064v3.pdf
https://github.com/vaynexie/CausalX-ViT
true
true
true
pytorch
https://paperswithcode.com/paper/mura-large-dataset-for-abnormality-detection
MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs
1712.06957
http://arxiv.org/abs/1712.06957v4
http://arxiv.org/pdf/1712.06957v4.pdf
https://github.com/anirudh2019/MURA-xception-inceptionV2
false
false
true
tf
https://paperswithcode.com/paper/agglomerative-fast-super-paramagnetic
Agglomerative Likelihood Clustering
1908.00951
https://arxiv.org/abs/1908.00951v4
https://arxiv.org/pdf/1908.00951v4.pdf
https://github.com/tehraio/timeseries_gen
false
false
true
none
https://paperswithcode.com/paper/graph2mda-a-multi-modal-variational-graph
Graph2MDA: a multi-modal variational graph embedding model for predicting microbe-drug associations
2108.06338
https://arxiv.org/abs/2108.06338v1
https://arxiv.org/pdf/2108.06338v1.pdf
https://github.com/moen-hyb/Graph2MDA
true
false
false
tf
https://paperswithcode.com/paper/syntactic-parse-fusion
Syntactic Parse Fusion
null
https://aclanthology.org/D15-1160
https://aclanthology.org/D15-1160.pdf
https://github.com/BLLIP/bllip-parser
true
true
false
none
https://paperswithcode.com/paper/improved-techniques-for-model-inversion-1
Knowledge-Enriched Distributional Model Inversion Attacks
2010.04092
https://arxiv.org/abs/2010.04092v4
https://arxiv.org/pdf/2010.04092v4.pdf
https://github.com/scccc21/knowledge-enriched-dmi
true
true
true
pytorch