Every paper with a summary

Every arXiv paper Paperlayer has summarized so far. Open any of them to read the summary beside the original PDF, with every point linked to the line, figure, or table it came from.

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23,761 to 23,820 of 61,350

Quantifying causal influences
Dominik Janzing, David Balduzzi, Moritz Grosse-Wentrup +1
math.STarXiv:1203.6502v22012
Quantum Approximate Optimization Algorithm: Performance, Mechanism, and Implementation on Near-Term Devices
Leo Zhou, Sheng-Tao Wang, Soonwon Choi +2
quant-phcond-mat.dis-nncond-mat.stat-mecharXiv:1812.01041v22018
Graph Neural Networks for Social Recommendation
Wenqi Fan, Yao Ma, Qing Li +4
cs.IRcs.LGcs.SIarXiv:1902.07243v22019
Adaptive Gradient Methods with Dynamic Bound of Learning Rate
Liangchen Luo, Yuanhao Xiong, Yan Liu +1
cs.LGstat.MLarXiv:1902.09843v12019
Joint Base Station Clustering and Beamformer Design for Partial Coordinated Transmission in Heterogenous Networks
Mingyi Hong, Ruo-Yu Sun, Hadi Baligh +1
cs.ITarXiv:1203.6390v32012
Theoretically Principled Trade-off between Robustness and Accuracy
Hongyang Zhang, Yaodong Yu, Jiantao Jiao +3
cs.LGstat.MLarXiv:1901.08573v32019
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data
Yinhao Zhu, Nicholas Zabaras, Phaedon-Stelios Koutsourelakis +1
physics.comp-phcs.CVcs.LGarXiv:1901.06314v12019
Hybrid Recommender Systems: A Systematic Literature Review
Erion Çano, Maurizio Morisio
cs.IRcs.CYcs.LGarXiv:1901.03888v12019
A Survey of Unsupervised Deep Domain Adaptation
Garrett Wilson, Diane J. Cook
cs.LGstat.MLarXiv:1812.02849v32018
Soft Actor-Critic Algorithms and Applications
Tuomas Haarnoja, Aurick Zhou, Kristian Hartikainen +8
cs.LGcs.AIcs.ROarXiv:1812.05905v22018
e-SNLI: Natural Language Inference with Natural Language Explanations
Oana-Maria Camburu, Tim Rocktäschel, Thomas Lukasiewicz +1
cs.CLarXiv:1812.01193v22018
Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile
Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati +3
cs.LGcs.GTmath.OCarXiv:1807.02629v22018
Validating quantum computers using randomized model circuits
Andrew W. Cross, Lev S. Bishop, Sarah Sheldon +2
quant-pharXiv:1811.12926v22018
Bilby: A user-friendly Bayesian inference library for gravitational-wave astronomy
Gregory Ashton, Moritz Huebner, Paul D. Lasky +18
astro-ph.IMastro-ph.HEgr-qcarXiv:1811.02042v12018
GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition
Hanqing Chao, Yiwei He, Junping Zhang +1
cs.CVarXiv:1811.06186v42018
Peer-to-peer and community-based markets: A comprehensive review
Tiago Sousa, Tiago Soares, Pierre Pinson +3
cs.CYarXiv:1810.09859v22018
Deep Neural Networks for Estimation and Inference
Max H. Farrell, Tengyuan Liang, Sanjog Misra
econ.EMcs.LGmath.STarXiv:1809.09953v32018
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
Jacob R. Gardner, Geoff Pleiss, David Bindel +2
cs.LGstat.MLarXiv:1809.11165v62018
Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips
Man Yao, Jiakui Hu, Tianxiang Hu +5
cs.NEcs.CVarXiv:2404.03663v12024
Gradient Descent Provably Optimizes Over-parameterized Neural Networks
Simon S. Du, Xiyu Zhai, Barnabas Poczos +1
cs.LGmath.OCstat.MLarXiv:1810.02054v22018
Learning deep representations by mutual information estimation and maximization
R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon +4
stat.MLcs.LGarXiv:1808.06670v52018
Direct Training for Spiking Neural Networks: Faster, Larger, Better
Yujie Wu, Lei Deng, Guoqi Li +2
cs.NEarXiv:1809.05793v22018
Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning
Hao Yu, Sen Yang, Shenghuo Zhu
math.OCcs.DCcs.LGarXiv:1807.06629v32018
Active sequential hypothesis testing
Mohammad Naghshvar, Tara Javidi
cs.ITmath.OCmath.STarXiv:1203.4626v42012
Degrees of Freedom of Time Correlated MISO Broadcast Channel with Delayed CSIT
Sheng Yang, Mari Kobayashi, David Gesbert +1
cs.ITarXiv:1203.2550v22012
The relativistic discriminator: a key element missing from standard GAN
Alexia Jolicoeur-Martineau
cs.LGcs.AIcs.CRarXiv:1807.00734v32018
Understanding Batch Normalization
Johan Bjorck, Carla Gomes, Bart Selman +1
cs.LGcs.AIstat.MLarXiv:1806.02375v42018
DARTS: Differentiable Architecture Search
Hanxiao Liu, Karen Simonyan, Yiming Yang
cs.LGcs.CLcs.CVarXiv:1806.09055v22018
A General Framework for Inference-time Scaling and Steering of Diffusion Models
Raghav Singhal, Zachary Horvitz, Ryan Teehan +4
cs.LGcs.CLcs.CVarXiv:2501.06848v52025
Deep Sequence Learning with Auxiliary Information for Traffic Prediction
Binbing Liao, Jingqing Zhang, Chao Wu +5
cs.CVcs.AIarXiv:1806.07380v12018
On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport
Lenaic Chizat, Francis Bach
math.OCcs.NEstat.MLarXiv:1805.09545v22018
Robustness May Be at Odds with Accuracy
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom +2
stat.MLcs.CVcs.LGarXiv:1805.12152v52018
TADAM: Task dependent adaptive metric for improved few-shot learning
Boris N. Oreshkin, Pau Rodriguez, Alexandre Lacoste
cs.LGcs.AIcs.CVarXiv:1805.10123v42018
Hyperbolic Neural Networks
Octavian-Eugen Ganea, Gary Bécigneul, Thomas Hofmann
cs.LGstat.MLarXiv:1805.09112v22018
Data-Efficient Hierarchical Reinforcement Learning
Ofir Nachum, Shixiang Gu, Honglak Lee +1
cs.LGcs.AIstat.MLarXiv:1805.08296v42018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
Dong Yin, Yudong Chen, Kannan Ramchandran +1
cs.LGcs.CRcs.DCarXiv:1803.01498v22018
Scalable Private Learning with PATE
Nicolas Papernot, Shuang Song, Ilya Mironov +3
stat.MLcs.CRcs.LGarXiv:1802.08908v12018
Selective Experience Replay for Lifelong Learning
David Isele, Akansel Cosgun
cs.AIarXiv:1802.10269v12018
Adversarially Learned One-Class Classifier for Novelty Detection
Mohammad Sabokrou, Mohammad Khalooei, Mahmood Fathy +1
cs.CVarXiv:1802.09088v22018
Fairness of Exposure in Rankings
Ashudeep Singh, Thorsten Joachims
cs.IRcs.CYarXiv:1802.07281v22018
A Survey on the Security of Blockchain Systems
Xiaoqi Li, Peng Jiang, Ting Chen +2
cs.CRarXiv:1802.06993v32018
Sparsity in multiple kernel learning
Vladimir Koltchinskii, Ming Yuan
math.STarXiv:1211.2998v12012
Mean Field Multi-Agent Reinforcement Learning
Yaodong Yang, Rui Luo, Minne Li +3
cs.MAcs.AIcs.LGarXiv:1802.05438v52018
PCoMoE: Shifting MoE Inference from Monolithic Expert Selection to Fine-Grained Path Composition
Ziyan Gan, Fangxin Liu, Chenyang Guan +10
cs.CLarXiv:2609.01024v12026
Optimal approximation of continuous functions by very deep ReLU networks
Dmitry Yarotsky
cs.NEarXiv:1802.03620v22018
Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification
Yinhao Zhu, Nicholas Zabaras
physics.comp-phcs.CVcs.LGarXiv:1801.06879v12018
Reasoning with Latent Thoughts: On the Power of Looped Transformers
Nikunj Saunshi, Nishanth Dikkala, Zhiyuan Li +2
cs.CLcs.AIcs.LGarXiv:2502.17416v12025
Demystifying MMD GANs
Mikołaj Bińkowski, Danica J. Sutherland, Michael Arbel +1
stat.MLcs.LGarXiv:1801.01401v52018
BestConfig: Tapping the Performance Potential of Systems via Automatic Configuration Tuning
Yuqing Zhu, Jianxun Liu, Mengying Guo +5
cs.PFcs.DBcs.DCarXiv:1710.03439v12017
Scale-free networks are rare
Anna D. Broido, Aaron Clauset
physics.soc-phcs.SIphysics.data-anarXiv:1801.03400v12018
Quasi-Oracle Estimation of Heterogeneous Treatment Effects
Xinkun Nie, Stefan Wager
stat.MLecon.EMmath.STarXiv:1712.04912v42017
Size-Independent Sample Complexity of Neural Networks
Noah Golowich, Alexander Rakhlin, Ohad Shamir
cs.LGcs.NEstat.MLarXiv:1712.06541v52017
REPA-E: Unlocking VAE for End-to-End Tuning with Latent Diffusion Transformers
Xingjian Leng, Jaskirat Singh, Yunzhong Hou +3
cs.CVcs.LGarXiv:2504.10483v32025
Distributed Observers Design for Leader-Following Control of Multi-Agent Networks (Extended Version)
Yiguang Hong, Guanrong Chen, Linda Bushnell
math.OCarXiv:1801.00258v12017
Towards Accurate Binary Convolutional Neural Network
Xiaofan Lin, Cong Zhao, Wei Pan
cs.LGstat.MLarXiv:1711.11294v12017
Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge
Emmanuel de Bezenac, Arthur Pajot, Patrick Gallinari
cs.AIcs.LGstat.MLarXiv:1711.07970v22017
Weakly-Supervised Neural Text Classification
Yu Meng, Jiaming Shen, Chao Zhang +1
cs.IRcs.CLcs.LGarXiv:1809.01478v22018
Quaternion kinematics for the error-state Kalman filter
Joan Solà
cs.ROarXiv:1711.02508v12017
Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition
Chris Donahue, Bo Li, Rohit Prabhavalkar
cs.SDcs.LGcs.NEarXiv:1711.05747v22017
The PseudoDojo: Training and grading a 85 element optimized norm-conserving pseudopotential table
M. J. van Setten, M. Giantomassi, E. Bousquet +4
cond-mat.mtrl-sciarXiv:1710.10138v22017

Every paper with a summary

Quantifying causal influences

Quantum Approximate Optimization Algorithm: Performance, Mechanism, and Implementation on Near-Term Devices

Graph Neural Networks for Social Recommendation

Adaptive Gradient Methods with Dynamic Bound of Learning Rate

Joint Base Station Clustering and Beamformer Design for Partial Coordinated Transmission in Heterogenous Networks

Theoretically Principled Trade-off between Robustness and Accuracy

Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data

Hybrid Recommender Systems: A Systematic Literature Review

A Survey of Unsupervised Deep Domain Adaptation

Soft Actor-Critic Algorithms and Applications

e-SNLI: Natural Language Inference with Natural Language Explanations

Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile

Validating quantum computers using randomized model circuits

Bilby: A user-friendly Bayesian inference library for gravitational-wave astronomy

GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition

Peer-to-peer and community-based markets: A comprehensive review

Deep Neural Networks for Estimation and Inference

GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips

Gradient Descent Provably Optimizes Over-parameterized Neural Networks

Learning deep representations by mutual information estimation and maximization

Direct Training for Spiking Neural Networks: Faster, Larger, Better

Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning

Active sequential hypothesis testing

Degrees of Freedom of Time Correlated MISO Broadcast Channel with Delayed CSIT

The relativistic discriminator: a key element missing from standard GAN

Understanding Batch Normalization

DARTS: Differentiable Architecture Search

A General Framework for Inference-time Scaling and Steering of Diffusion Models

Deep Sequence Learning with Auxiliary Information for Traffic Prediction

On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport

Robustness May Be at Odds with Accuracy

TADAM: Task dependent adaptive metric for improved few-shot learning

Hyperbolic Neural Networks

Data-Efficient Hierarchical Reinforcement Learning

Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates

Scalable Private Learning with PATE

Selective Experience Replay for Lifelong Learning

Adversarially Learned One-Class Classifier for Novelty Detection

Fairness of Exposure in Rankings

A Survey on the Security of Blockchain Systems

Sparsity in multiple kernel learning

Mean Field Multi-Agent Reinforcement Learning

PCoMoE: Shifting MoE Inference from Monolithic Expert Selection to Fine-Grained Path Composition

Optimal approximation of continuous functions by very deep ReLU networks

Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification

Reasoning with Latent Thoughts: On the Power of Looped Transformers

Demystifying MMD GANs

BestConfig: Tapping the Performance Potential of Systems via Automatic Configuration Tuning

Scale-free networks are rare

Quasi-Oracle Estimation of Heterogeneous Treatment Effects

Size-Independent Sample Complexity of Neural Networks

REPA-E: Unlocking VAE for End-to-End Tuning with Latent Diffusion Transformers

Distributed Observers Design for Leader-Following Control of Multi-Agent Networks (Extended Version)

Towards Accurate Binary Convolutional Neural Network

Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge

Weakly-Supervised Neural Text Classification

Quaternion kinematics for the error-state Kalman filter

Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition

The PseudoDojo: Training and grading a 85 element optimized norm-conserving pseudopotential table