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

Dataset card Data Studio Files
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Community
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https://paperswithcode.com/paper/dynamic-programming-based-failure-tolerant
Dynamic-Programming-Based Failure-Tolerant Control for Satellite with Thrusters in 6-DOF Motion
2110.00783
https://arxiv.org/abs/2110.00783v1
https://arxiv.org/pdf/2110.00783v1.pdf
https://github.com/abdolrezat/SPHERES-DPcontrol
true
false
false
none
https://paperswithcode.com/paper/improving-multi-turn-dialogue-modelling-with
Improving Multi-turn Dialogue Modelling with Utterance ReWriter
1906.07004
https://arxiv.org/abs/1906.07004v1
https://arxiv.org/pdf/1906.07004v1.pdf
https://github.com/chin-gyou/dialogue-utterance-rewriter
false
false
true
tf
https://paperswithcode.com/paper/the-wili-benchmark-dataset-for-written
The WiLI benchmark dataset for written language identification
1801.07779
http://arxiv.org/abs/1801.07779v1
http://arxiv.org/pdf/1801.07779v1.pdf
https://github.com/LauraRuis/LanguageIdentification
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/MalayAgr/DeepNeuralNetwork-Scratch
false
false
false
tf
https://paperswithcode.com/paper/pysbd-pragmatic-sentence-boundary
PySBD: Pragmatic Sentence Boundary Disambiguation
2010.09657
https://arxiv.org/abs/2010.09657v1
https://arxiv.org/pdf/2010.09657v1.pdf
https://github.com/nipunsadvilkar/pySBD
true
true
true
none
https://paperswithcode.com/paper/mask-gvae-blind-denoising-graphs-via
Mask-GVAE: Blind Denoising Graphs via Partition
2102.04228
https://arxiv.org/abs/2102.04228v1
https://arxiv.org/pdf/2102.04228v1.pdf
https://github.com/halimiqi/www21
false
false
false
tf
https://paperswithcode.com/paper/bootstrapping-relation-extractors-using
Bootstrapping Relation Extractors using Syntactic Search by Examples
2102.05007
https://arxiv.org/abs/2102.05007v1
https://arxiv.org/pdf/2102.05007v1.pdf
https://github.com/mataney/BootstrappingRelationExtractors
true
true
false
pytorch
https://paperswithcode.com/paper/hold-me-tight-influence-of-discriminative
Hold me tight! Influence of discriminative features on deep network boundaries
2002.06349
https://arxiv.org/abs/2002.06349v4
https://arxiv.org/pdf/2002.06349v4.pdf
https://github.com/LTS4/hold-me-tight
true
true
true
pytorch
https://paperswithcode.com/paper/on-the-cross-lingual-transferability-of
On the Cross-lingual Transferability of Monolingual Representations
1910.11856
https://arxiv.org/abs/1910.11856v3
https://arxiv.org/pdf/1910.11856v3.pdf
https://github.com/alon-albalak/xor-covid
false
false
true
pytorch
https://paperswithcode.com/paper/towards-expressive-graph-representation
Towards Expressive Graph Representation
2010.05427
https://arxiv.org/abs/2010.05427v1
https://arxiv.org/pdf/2010.05427v1.pdf
https://github.com/mocherson/Exp_GNN
true
true
false
pytorch
https://paperswithcode.com/paper/hint3-raising-the-bar-for-intent-detection-in
HINT3: Raising the bar for Intent Detection in the Wild
2009.13833
https://arxiv.org/abs/2009.13833v2
https://arxiv.org/pdf/2009.13833v2.pdf
https://github.com/hellohaptik/HINT3
true
true
true
none
https://paperswithcode.com/paper/knowledge-enhanced-personalized-review
Knowledge-Enhanced Personalized Review Generation with Capsule Graph Neural Network
2010.01480
https://arxiv.org/abs/2010.01480v1
https://arxiv.org/pdf/2010.01480v1.pdf
https://github.com/turboLJY/CapsGNN-Review-Generation
true
false
true
pytorch
https://paperswithcode.com/paper/cad2render-a-modular-toolkit-for-gpu
CAD2Render: A Modular Toolkit for GPU-accelerated Photorealistic Synthetic Data Generation for the Manufacturing Industry
2211.14054
https://arxiv.org/abs/2211.14054v1
https://arxiv.org/pdf/2211.14054v1.pdf
https://github.com/edm-research/cad2render
true
true
false
none
https://paperswithcode.com/paper/towards-evaluating-the-robustness-of-neural
Towards Evaluating the Robustness of Neural Networks
1608.04644
http://arxiv.org/abs/1608.04644v2
http://arxiv.org/pdf/1608.04644v2.pdf
https://github.com/SifatMd/Research-Papers
false
false
true
none
https://paperswithcode.com/paper/morphable-detector-for-object-detection-on-1
Morphable Detector for Object Detection on Demand
2110.04917
https://arxiv.org/abs/2110.04917v1
https://arxiv.org/pdf/2110.04917v1.pdf
https://github.com/zhaoxiangyun/morphable-detector
true
true
true
pytorch
https://paperswithcode.com/paper/continuous-control-with-deep-reinforcement
Continuous control with deep reinforcement learning
1509.02971
https://arxiv.org/abs/1509.02971v6
https://arxiv.org/pdf/1509.02971v6.pdf
https://github.com/DLR-RM/stable-baselines3
false
false
false
pytorch
https://paperswithcode.com/paper/u-2-net-going-deeper-with-nested-u-structure
U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection
2005.09007
https://arxiv.org/abs/2005.09007v3
https://arxiv.org/pdf/2005.09007v3.pdf
https://github.com/xuebinqin/U-2-Net
false
false
true
pytorch
https://paperswithcode.com/paper/low-dimensional-manifolds-support-multiplexed
Low-Dimensional Manifolds Support Multiplexed Integrations in Recurrent Neural Networks
2011.10435
https://arxiv.org/abs/2011.10435v1
https://arxiv.org/pdf/2011.10435v1.pdf
https://github.com/AFanthomme/ManifoldsSupportRNI
true
true
false
pytorch
https://paperswithcode.com/paper/a-simple-neural-network-module-for-relational
A simple neural network module for relational reasoning
1706.01427
http://arxiv.org/abs/1706.01427v1
http://arxiv.org/pdf/1706.01427v1.pdf
https://github.com/jaehyunnn/RelationalNetwork_pytorch
false
false
true
pytorch
https://paperswithcode.com/paper/language-through-a-prism-a-spectral-approach
Language Through a Prism: A Spectral Approach for Multiscale Language Representations
2011.04823
https://arxiv.org/abs/2011.04823v1
https://arxiv.org/pdf/2011.04823v1.pdf
https://github.com/zh217/torch-dct
false
true
false
pytorch
https://paperswithcode.com/paper/you2me-inferring-body-pose-in-egocentric
You2Me: Inferring Body Pose in Egocentric Video via First and Second Person Interactions
1904.09882
https://arxiv.org/abs/1904.09882v2
https://arxiv.org/pdf/1904.09882v2.pdf
https://github.com/facebookresearch/you2me
true
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/zhuchen03/maxva
false
false
true
pytorch
https://paperswithcode.com/paper/reducing-bert-pre-training-time-from-3-days
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes
1904.00962
https://arxiv.org/abs/1904.00962v5
https://arxiv.org/pdf/1904.00962v5.pdf
https://github.com/zhuchen03/maxva
false
false
true
pytorch
https://paperswithcode.com/paper/neural-codec-language-models-are-zero-shot
Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
2301.02111
https://arxiv.org/abs/2301.02111v1
https://arxiv.org/pdf/2301.02111v1.pdf
https://github.com/enhuiz/vall-e
false
false
false
pytorch
https://paperswithcode.com/paper/kervolutional-neural-networks
Kervolutional Neural Networks
1904.03955
https://arxiv.org/abs/1904.03955v2
https://arxiv.org/pdf/1904.03955v2.pdf
https://github.com/liuch37/Kerception
false
false
true
tf
https://paperswithcode.com/paper/what-did-you-think-would-happen-explaining
What Did You Think Would Happen? Explaining Agent Behaviour Through Intended Outcomes
2011.05064
https://arxiv.org/abs/2011.05064v1
https://arxiv.org/pdf/2011.05064v1.pdf
https://github.com/hmhyau/rl-intention
true
true
false
pytorch
https://paperswithcode.com/paper/coarse-to-fine-pre-training-for-named-entity
Coarse-to-Fine Pre-training for Named Entity Recognition
2010.08210
https://arxiv.org/abs/2010.08210v1
https://arxiv.org/pdf/2010.08210v1.pdf
https://github.com/strawberryx/CoFEE
true
true
false
pytorch
https://paperswithcode.com/paper/generative-adversarial-network-to-learn-valid
Learning Constrained Distributions of Robot Configurations with Generative Adversarial Network
2011.05717
https://arxiv.org/abs/2011.05717v2
https://arxiv.org/pdf/2011.05717v2.pdf
https://github.com/teguhSL/learning_distribution_gan
true
true
false
tf
https://paperswithcode.com/paper/fc-dcnn-a-densely-connected-neural-network
FC-DCNN: A densely connected neural network for stereo estimation
2010.06950
https://arxiv.org/abs/2010.06950v1
https://arxiv.org/pdf/2010.06950v1.pdf
https://github.com/thedodo/FC-DCNN2
true
false
true
pytorch
https://paperswithcode.com/paper/acorns-an-easy-to-use-code-generator-for
ACORNS: An Easy-To-Use Code Generator for Gradients and Hessians
2007.05094
https://arxiv.org/abs/2007.05094v1
https://arxiv.org/pdf/2007.05094v1.pdf
https://github.com/deshanadesai/acorns
true
true
false
none
https://paperswithcode.com/paper/towards-practical-control-of-singular-values
Towards Practical Control of Singular Values of Convolutional Layers
2211.13771
https://arxiv.org/abs/2211.13771v1
https://arxiv.org/pdf/2211.13771v1.pdf
https://github.com/whiteteadragon/practical_svd_conv
true
true
false
pytorch
https://paperswithcode.com/paper/a-simple-framework-for-contrastive-learning
A Simple Framework for Contrastive Learning of Visual Representations
2002.05709
https://arxiv.org/abs/2002.05709v3
https://arxiv.org/pdf/2002.05709v3.pdf
https://github.com/danielzgsilva/MOT
false
false
true
pytorch
https://paperswithcode.com/paper/solving-geometry-problems-combining-text-and
Solving Geometry Problems: Combining Text and Diagram Interpretation
null
https://aclanthology.org/D15-1171
https://aclanthology.org/D15-1171.pdf
https://github.com/uwnlp/geosolver
true
false
false
none
https://paperswithcode.com/paper/recfa-resilient-control-flow-attestation
ReCFA: Resilient Control-Flow Attestation
2110.11603
https://arxiv.org/abs/2110.11603v3
https://arxiv.org/pdf/2110.11603v3.pdf
https://github.com/suncongxd/recfa
true
true
false
none
https://paperswithcode.com/paper/image-classification-by-reinforcement
Image Classification by Reinforcement Learning with Two-State Q-Learning
2007.01298
https://arxiv.org/abs/2007.01298v3
https://arxiv.org/pdf/2007.01298v3.pdf
https://github.com/ilonatommy/DLR_FacialEmotionRecognition
false
false
true
none
https://paperswithcode.com/paper/end-user-programming-of-low-and-high-level
End-User Programming of Low- and High-Level Actions for Robotic Task Planning
2103.14342
https://arxiv.org/abs/2103.14342v1
https://arxiv.org/pdf/2103.14342v1.pdf
https://github.com/ysl208/iRoPro
true
true
false
none
https://paperswithcode.com/paper/out-of-distribution-detection-with-semantic
Out-of-Distribution Detection with Semantic Mismatch under Masking
2208.00446
https://arxiv.org/abs/2208.00446v1
https://arxiv.org/pdf/2208.00446v1.pdf
https://github.com/cure-lab/moodcat
true
true
false
pytorch
https://paperswithcode.com/paper/meld-a-multimodal-multi-party-dataset-for
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
1810.02508
https://arxiv.org/abs/1810.02508v6
https://arxiv.org/pdf/1810.02508v6.pdf
https://github.com/songys/KosentimentalTreebank
false
false
true
none
https://paperswithcode.com/paper/generative-adversarial-imitation-learning
Generative Adversarial Imitation Learning
1606.03476
http://arxiv.org/abs/1606.03476v1
http://arxiv.org/pdf/1606.03476v1.pdf
https://github.com/opendilab/DI-engine/blob/main/ding/reward_model/gail_irl_model.py
false
false
false
pytorch
https://paperswithcode.com/paper/topologically-driven-methods-for-construction
Topologically Driven Methods for Construction Of Multi-Edge Type (Multigraph with nodes puncturing) Quasi-Cyclic Low-density Parity-check Codes for Wireless Channel, WDM Long-Haul and Archival Holographic Memory
2011.14753
https://arxiv.org/abs/2011.14753v3
https://arxiv.org/pdf/2011.14753v3.pdf
https://github.com/Lcrypto/-Greedy-Guess-and-Test-method-for-construction-QC-LDPC-codes-with-CPM-of-weigth-more-than-1.
true
false
false
none
https://paperswithcode.com/paper/inferring-networks-of-substitutable-and
Inferring Networks of Substitutable and Complementary Products
1506.08839
http://arxiv.org/abs/1506.08839v1
http://arxiv.org/pdf/1506.08839v1.pdf
https://github.com/snap-stanford/snap
true
false
false
none
https://paperswithcode.com/paper/towards-low-resource-harmful-meme-detection
Towards Low-Resource Harmful Meme Detection with LMM Agents
2411.05383
https://arxiv.org/abs/2411.05383v1
https://arxiv.org/pdf/2411.05383v1.pdf
https://github.com/jianzhao-huang/lorehm
true
true
false
pytorch
https://paperswithcode.com/paper/developers-perception-fixed-bugs-often
Developers' Perception: Fixed Bugs Often Overlooked as Quality Contributions
2403.10806
https://arxiv.org/abs/2403.10806v1
https://arxiv.org/pdf/2403.10806v1.pdf
https://github.com/system205/questionnairedata
true
true
false
none
https://paperswithcode.com/paper/recurrent-rational-networks
Adaptive Rational Activations to Boost Deep Reinforcement Learning
2102.09407
https://arxiv.org/abs/2102.09407v5
https://arxiv.org/pdf/2102.09407v5.pdf
https://github.com/ml-research/rational_sl
true
true
true
pytorch
https://paperswithcode.com/paper/darf-a-data-reduced-fade-version-for
DARF: A data-reduced FADE version for simulations of speech recognition thresholds with real hearing aids
2007.05378
https://arxiv.org/abs/2007.05378v3
https://arxiv.org/pdf/2007.05378v3.pdf
https://github.com/m-r-s/fade
true
false
false
none
https://paperswithcode.com/paper/data-efficient-reinforcement-learning-with
Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control
1706.06491
http://arxiv.org/abs/1706.06491v2
http://arxiv.org/pdf/1706.06491v2.pdf
https://github.com/SimonRennotte/Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control
false
false
true
pytorch
https://paperswithcode.com/paper/elixir-learning-from-user-feedback-on
ELIXIR: Learning from User Feedback on Explanations to Improve Recommender Models
2102.09388
https://arxiv.org/abs/2102.09388v3
https://arxiv.org/pdf/2102.09388v3.pdf
https://github.com/azinmatin/elixir
true
true
false
none
https://paperswithcode.com/paper/unveiling-the-potential-of-structure
Unveiling the Potential of Structure Preserving for Weakly Supervised Object Localization
2103.04523
https://arxiv.org/abs/2103.04523v2
https://arxiv.org/pdf/2103.04523v2.pdf
https://github.com/Panxjia/SPA_CVPR2021
true
true
true
pytorch
https://paperswithcode.com/paper/tlmote-a-topic-based-language-modelling
TLMOTE: A Topic-based Language Modelling Approach for Text Oversampling
null
https://journals.flvc.org/FLAIRS/article/view/130676
https://journals.flvc.org/FLAIRS/article/view/130676/133877
https://github.com/Arjun7m/TLMOTE
true
false
false
none
https://paperswithcode.com/paper/bert-pre-training-of-deep-bidirectional
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
1810.04805
https://arxiv.org/abs/1810.04805v2
https://arxiv.org/pdf/1810.04805v2.pdf
https://github.com/teghub/TurkishNER-BERT
false
false
true
tf
https://paperswithcode.com/paper/ladder-variational-autoencoders
Ladder Variational Autoencoders
1602.02282
http://arxiv.org/abs/1602.02282v3
http://arxiv.org/pdf/1602.02282v3.pdf
https://github.com/addtt/ladder-vae-pytorch
false
false
false
pytorch
https://paperswithcode.com/paper/multi-study-factor-analysis
Multi-study Factor Analysis
1611.06350
http://arxiv.org/abs/1611.06350v3
http://arxiv.org/pdf/1611.06350v3.pdf
https://github.com/rdevito/MSFA
true
true
false
none
https://paperswithcode.com/paper/accelerating-cross-validation-with-total
Accelerating cross-validation with total variation and its application to super-resolution imaging
1611.07197
http://arxiv.org/abs/1611.07197v2
http://arxiv.org/pdf/1611.07197v2.pdf
https://github.com/T-Obuchi/AcceleratedCVon2DTVLR
true
true
false
none
https://paperswithcode.com/paper/generalized-sampling-in-julia
Generalized Sampling in Julia
1607.04091
http://arxiv.org/abs/1607.04091v2
http://arxiv.org/pdf/1607.04091v2.pdf
https://github.com/robertdj/GeneralizedSampling.jl
true
true
false
none
https://paperswithcode.com/paper/pinpointing-delay-and-forwarding-anomalies
Pinpointing Delay and Forwarding Anomalies Using Large-Scale Traceroute Measurements
1605.04784
http://arxiv.org/abs/1605.04784v2
http://arxiv.org/pdf/1605.04784v2.pdf
https://github.com/romain-fontugne/tartiflette
true
true
false
none
https://paperswithcode.com/paper/applying-bayesian-parameter-estimation-to
Applying Bayesian parameter estimation to relativistic heavy-ion collisions: simultaneous characterization of the initial state and quark-gluon plasma medium
1605.03954
http://arxiv.org/abs/1605.03954v2
http://arxiv.org/pdf/1605.03954v2.pdf
https://github.com/Duke-QCD/trento-paper-2
true
true
false
none
https://paperswithcode.com/paper/a-context-oriented-extension-of-f
A Context-Oriented Extension of F#
1512.07681
http://arxiv.org/abs/1512.07681v1
http://arxiv.org/pdf/1512.07681v1.pdf
https://github.com/vslab/fscoda
true
true
false
none
https://paperswithcode.com/paper/190100897
Please Forget Where I Was Last Summer: The Privacy Risks of Public Location (Meta)Data
1901.00897
http://arxiv.org/abs/1901.00897v1
http://arxiv.org/pdf/1901.00897v1.pdf
https://github.com/r3mlab/tweetsmapper
false
false
true
none
https://paperswithcode.com/paper/observables-of-qcd-diffraction
Observables of QCD Diffraction
1612.00980
http://arxiv.org/abs/1612.00980v2
http://arxiv.org/pdf/1612.00980v2.pdf
https://github.com/mieskolainen/Diffractive-Combinatorics
false
false
true
none
https://paperswithcode.com/paper/190412818
A planetary system around the nearby M dwarf Gl 357 including a transiting hot Earth-sized planet optimal for atmospheric characterisation
1904.12818
http://arxiv.org/abs/1904.12818v1
http://arxiv.org/pdf/1904.12818v1.pdf
https://github.com/hpparvi/Gl_357_TTV_analysis
false
false
true
none
https://paperswithcode.com/paper/stability-of-surface-contacts-for-humanoid
Stability of Surface Contacts for Humanoid Robots: Closed-Form Formulae of the Contact Wrench Cone for Rectangular Support Areas
1501.04719
http://arxiv.org/abs/1501.04719v1
http://arxiv.org/pdf/1501.04719v1.pdf
https://github.com/stephane-caron/analytical-wrench-cone
false
false
true
none
https://paperswithcode.com/paper/betting-and-belief-prediction-markets-and
Betting and Belief: Prediction Markets and Attribution of Climate Change
1603.08961
http://arxiv.org/abs/1603.08961v3
http://arxiv.org/pdf/1603.08961v3.pdf
https://github.com/JohnNay/predMarket
true
true
true
none
https://paperswithcode.com/paper/yolox-pai-an-improved-yolox-version-by-pai
YOLOX-PAI: An Improved YOLOX, Stronger and Faster than YOLOv6
2208.13040
https://arxiv.org/abs/2208.13040v3
https://arxiv.org/pdf/2208.13040v3.pdf
https://github.com/code-implementation1/Code9/tree/main/YOLOX
false
false
false
mindspore
https://paperswithcode.com/paper/zmp-support-areas-for-multi-contact-mobility
ZMP support areas for multi-contact mobility under frictional constraints
1510.03232
http://arxiv.org/abs/1510.03232v2
http://arxiv.org/pdf/1510.03232v2.pdf
https://github.com/stephane-caron/tro-2016
true
true
true
none
https://paperswithcode.com/paper/robust-parameter-determination-in-epidemic
Robust parameter determination in epidemic models with analytical descriptions of uncertainties
1807.05301
http://arxiv.org/abs/1807.05301v1
http://arxiv.org/pdf/1807.05301v1.pdf
https://github.com/GallupGovt/multivac
false
false
true
pytorch
https://paperswithcode.com/paper/time-domain-neural-audio-style-transfer
Time Domain Neural Audio Style Transfer
1711.11160
http://arxiv.org/abs/1711.11160v1
http://arxiv.org/pdf/1711.11160v1.pdf
https://github.com/pkmital/time-domain-neural-audio-style-transfer
false
false
true
tf
https://paperswithcode.com/paper/fast-penalized-regression-and-cross
Fast Penalized Regression and Cross Validation for Tall Data with the oem Package
1801.09661
http://arxiv.org/abs/1801.09661v1
http://arxiv.org/pdf/1801.09661v1.pdf
https://github.com/jaredhuling/oem
false
false
true
none
https://paperswithcode.com/paper/discovery-and-validation-of-a-high-density
Discovery and Validation of a High-Density sub-Neptune from the K2 Mission
1601.07608
http://arxiv.org/abs/1601.07608v2
http://arxiv.org/pdf/1601.07608v2.pdf
https://github.com/nespinoza/exonailer
true
true
true
none
https://paperswithcode.com/paper/markov-chain-monte-carlo-population-synthesis
Markov chain Monte Carlo population synthesis of single radio pulsars in the Galaxy
1803.02397
http://arxiv.org/abs/1803.02397v1
http://arxiv.org/pdf/1803.02397v1.pdf
https://github.com/cieslar/Indri
true
true
true
none
https://paperswithcode.com/paper/full-covariance-of-cmb-and-lensing
Full covariance of CMB and lensing reconstruction power spectra
1611.01446
http://arxiv.org/abs/1611.01446v2
http://arxiv.org/pdf/1611.01446v2.pdf
https://github.com/JulienPeloton/lenscov
true
true
true
none
https://paperswithcode.com/paper/matrix-factorization-at-scale-a-comparison-of
Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies
1607.01335
http://arxiv.org/abs/1607.01335v3
http://arxiv.org/pdf/1607.01335v3.pdf
https://github.com/wushanshan/MatrixProductPCA
false
false
true
none
https://paperswithcode.com/paper/cognitive-capabilities-for-the-caai-in-cyber
Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems
2012.01823
https://arxiv.org/abs/2012.01823v1
https://arxiv.org/pdf/2012.01823v1.pdf
https://github.com/janstrohschein/KOARCH
true
true
false
none
https://paperswithcode.com/paper/peer-to-peer-hate-hate-speech-instigators-and
Peer to Peer Hate: Hate Speech Instigators and Their Targets
1804.04649
http://arxiv.org/abs/1804.04649v1
http://arxiv.org/pdf/1804.04649v1.pdf
https://github.com/mayelsherif/hate_speech_icwsm18
true
true
false
none
https://paperswithcode.com/paper/modelfactory-a-matlab-octave-based-toolbox-to
ModelFactory: A Matlab/Octave based toolbox to create human body models
1804.03407
http://arxiv.org/abs/1804.03407v2
http://arxiv.org/pdf/1804.03407v2.pdf
https://github.com/manishsreenivasa/ModelFactory
true
true
false
none
https://paperswithcode.com/paper/the-impact-of-automated-parameter
The Impact of Automated Parameter Optimization on Defect Prediction Models
1801.10270
http://arxiv.org/abs/1801.10270v1
http://arxiv.org/pdf/1801.10270v1.pdf
https://github.com/klainfo/ScottKnottESD
true
true
false
none
https://paperswithcode.com/paper/solving-systems-of-phaseless-equations-via
Solving systems of phaseless equations via Kaczmarz methods: A proof of concept study
1502.01822
http://arxiv.org/abs/1502.01822v3
http://arxiv.org/pdf/1502.01822v3.pdf
https://github.com/makwei/phase-kacz
true
true
false
none
https://paperswithcode.com/paper/bayesian-spike-inference-from-calcium-imaging
Bayesian spike inference from calcium imaging data
1311.6864
http://arxiv.org/abs/1311.6864v1
http://arxiv.org/pdf/1311.6864v1.pdf
https://github.com/epnev/continuous_time_ca_sampler
false
false
true
none
https://paperswithcode.com/paper/reconstructing-the-lensing-mass-in-the
Reconstructing the Lensing Mass in the Universe from Photometric Catalogue Data
1303.6564
https://arxiv.org/abs/1303.6564v1
https://arxiv.org/pdf/1303.6564v1.pdf
https://github.com/drphilmarshall/Pangloss
true
true
true
none
https://paperswithcode.com/paper/stability-approach-to-regularization-1
Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models
1006.3316
https://arxiv.org/abs/1006.3316v1
https://arxiv.org/pdf/1006.3316v1.pdf
https://github.com/zdk123/SpiecEasi
false
false
true
none
https://paperswithcode.com/paper/generalized-stability-approach-for
Generalized Stability Approach for Regularized Graphical Models
1605.07072
http://arxiv.org/abs/1605.07072v1
http://arxiv.org/pdf/1605.07072v1.pdf
https://github.com/zdk123/SpiecEasi
false
false
true
none
https://paperswithcode.com/paper/omni-gan-on-the-secrets-of-cgans-and-beyond
Omni-GAN: On the Secrets of cGANs and Beyond
2011.13074
https://arxiv.org/abs/2011.13074v3
https://arxiv.org/pdf/2011.13074v3.pdf
https://github.com/PeterouZh/Omni-GAN-PyTorch
true
true
true
pytorch
https://paperswithcode.com/paper/a-new-model-to-predict-weak-lensing-peak-1
A new model to predict weak-lensing peak counts II. Parameter constraint strategies
1506.01076
http://arxiv.org/abs/1506.01076v2
http://arxiv.org/pdf/1506.01076v2.pdf
https://github.com/Linc-tw/camelus
true
true
true
none
https://paperswithcode.com/paper/a-new-model-to-predict-weak-lensing-peak-2
A new model to predict weak-lensing peak counts III. Filtering technique comparisons
1603.06773
http://arxiv.org/abs/1603.06773v2
http://arxiv.org/pdf/1603.06773v2.pdf
https://github.com/Linc-tw/camelus
true
true
true
none
https://paperswithcode.com/paper/multi-view-analysis-of-unregistered-medical
Multi-view analysis of unregistered medical images using cross-view transformers
2103.11390
https://arxiv.org/abs/2103.11390v2
https://arxiv.org/pdf/2103.11390v2.pdf
https://github.com/gvtulder/cross-view-transformers
true
false
true
pytorch
https://paperswithcode.com/paper/sum-product-networks-for-robust-automatic
Sum-Product Networks for Robust Automatic Speaker Identification
1910.11969
http://arxiv.org/abs/1910.11969v3
http://arxiv.org/pdf/1910.11969v3.pdf
https://github.com/anicolson/SPN-ASI
true
true
true
tf
https://paperswithcode.com/paper/a-new-directional-algebraic-fast-multipole
A new Directional Algebraic Fast Multipole Method based iterative solver for the Lippmann-Schwinger equation accelerated with HODLR preconditioner
2204.00326
https://arxiv.org/abs/2204.00326v2
https://arxiv.org/pdf/2204.00326v2.pdf
https://github.com/vaishna77/lippmann_schwinger_solver
true
true
false
none
https://paperswithcode.com/paper/predrnn-towards-a-resolution-of-the-deep-in
PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning
1804.06300
http://arxiv.org/abs/1804.06300v2
http://arxiv.org/pdf/1804.06300v2.pdf
https://github.com/thuml/predrnn-pytorch
false
false
false
pytorch
https://paperswithcode.com/paper/fast-and-accurate-voronoi-density-gridding
Fast and accurate Voronoi density gridding from Lagrangian hydrodynamics data
1710.07108
http://arxiv.org/abs/1710.07108v2
http://arxiv.org/pdf/1710.07108v2.pdf
https://github.com/mapetkova/kernel-integration
true
true
true
none
https://paperswithcode.com/paper/pulp-hd-accelerating-brain-inspired-high
PULP-HD: Accelerating Brain-Inspired High-Dimensional Computing on a Parallel Ultra-Low Power Platform
1804.09123
http://arxiv.org/abs/1804.09123v1
http://arxiv.org/pdf/1804.09123v1.pdf
https://github.com/fabio-montagna/PULP-HD
true
true
false
none
https://paperswithcode.com/paper/a-data-driven-mcmillan-degree-lower-bound
A Data-Driven McMillan Degree Lower Bound
1803.00043
http://arxiv.org/abs/1803.00043v2
http://arxiv.org/pdf/1803.00043v2.pdf
https://github.com/jeffrey-hokanson/McMillanDegree
true
true
false
none
https://paperswithcode.com/paper/importance-sampling-for-partially-observed
Importance sampling for partially observed temporal epidemic models
1801.08244
http://arxiv.org/abs/1801.08244v2
http://arxiv.org/pdf/1801.08244v2.pdf
https://github.com/EpiStruct/Black-2018
true
true
false
none
https://paperswithcode.com/paper/accurate-and-efficient-surface-reconstruction
Accurate and efficient surface reconstruction from volume fraction data on general meshes
1801.05382
http://arxiv.org/abs/1801.05382v2
http://arxiv.org/pdf/1801.05382v2.pdf
https://github.com/DLR-RY/VoFLibrary
true
true
false
none
https://paperswithcode.com/paper/updating-probabilistic-knowledge-on-condition
Updating Probabilistic Knowledge on Condition/Event Nets using Bayesian Networks
1807.02566
http://arxiv.org/abs/1807.02566v1
http://arxiv.org/pdf/1807.02566v1.pdf
https://github.com/bencabrera/bayesian_nets_program
true
true
false
none
https://paperswithcode.com/paper/challenging-common-interpretability
Challenging common interpretability assumptions in feature attribution explanations
2012.02748
https://arxiv.org/abs/2012.02748v1
https://arxiv.org/pdf/2012.02748v1.pdf
https://git.sr.ht/~hyphaebeast/challenging-xai
true
false
false
none
https://paperswithcode.com/paper/a-novel-approach-for-ridge-detection-and-mode
A Novel Ridge Detector for Nonstationary Multicomponent Signals: Development and Application to Robust Mode Retrieval
2009.13123
https://arxiv.org/abs/2009.13123v2
https://arxiv.org/pdf/2009.13123v2.pdf
https://github.com/Nils-Laurent/RRP-RD
true
true
false
none
https://paperswithcode.com/paper/a-multiscale-scan-statistic-for-adaptive
A Multiscale Scan Statistic for Adaptive Submatrix Localization
1906.08884
http://arxiv.org/abs/1906.08884v1
http://arxiv.org/pdf/1906.08884v1.pdf
https://github.com/nozoeli/adaptiveBiclustering
true
true
false
none
https://paperswithcode.com/paper/buoyancy-driven-entrainment-in-dry-thermals
Buoyancy-Driven Entrainment in Dry Thermals
1906.07224
http://arxiv.org/abs/1906.07224v2
http://arxiv.org/pdf/1906.07224v2.pdf
https://github.com/mckimb/buoyant_entrainment
true
true
false
none
https://paperswithcode.com/paper/approximating-orthogonal-matrices-with
Approximating Orthogonal Matrices with Effective Givens Factorization
1905.05796
http://arxiv.org/abs/1905.05796v1
http://arxiv.org/pdf/1905.05796v1.pdf
https://github.com/tfrerix/givens-factorization
true
true
false
none
https://paperswithcode.com/paper/distributed-sampling-quantum-communication
Distributed sampling, quantum communication witnesses, and measurement incompatibility
1904.08435
http://arxiv.org/abs/1904.08435v4
http://arxiv.org/pdf/1904.08435v4.pdf
https://github.com/guerinileonardo/DS_QCwit_MI
true
true
false
none
https://paperswithcode.com/paper/collision-rates-of-planetesimals-near-mean
Collision rates of planetesimals near mean-motion resonances
2102.12537
https://arxiv.org/abs/2102.12537v1
https://arxiv.org/pdf/2102.12537v1.pdf
https://github.com/spencerw/planetesimal_coll_paper
true
true
false
none