Papers
11,955 papers found
Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD
Konstantinos Nikolakakis, Farzin Haddadpour, Amin Karbasi et al.
Bias Propagation in Federated Learning
Hongyan Chang, Reza Shokri
Bidirectional Language Models Are Also Few-shot Learners
Ajay Patel, Bryan Li, Mohammad Sadegh Rasooli et al.
BigVGAN: A Universal Neural Vocoder with Large-Scale Training
Sang-gil Lee, Wei Ping, Boris Ginsburg et al.
Bi-level Dynamic Learning for Jointly Multi-modality Image Fusion and Beyond
Zhu Liu, Jinyuan Liu, Guanyao Wu et al.
Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients
Zhongkai Hao, Chengyang Ying, Hang Su et al.
Binding Language Models in Symbolic Languages
Zhoujun Cheng, Tianbao Xie, Peng Shi et al.
Bispectral Neural Networks
Sophia Sanborn, Christian A Shewmake, Bruno Olshausen et al.
Bit-Pruning: A Sparse Multiplication-Less Dot-Product
Yusuke Sekikawa, Shingo Yashima
Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts
Amrith Setlur, Don Dennis, Benjamin Eysenbach et al.
Block and Subword-Scaling Floating-Point (BSFP) : An Efficient Non-Uniform Quantization For Low Precision Inference
Yun-Chen Lo, Tse-Kuang Lee, Ren-Shuo Liu
Blurring Diffusion Models
Emiel Hoogeboom, Tim Salimans
Boosting Adversarial Transferability using Dynamic Cues
Muzammal Naseer, Ahmad Mahmood, Salman Khan et al.
Boosting Causal Discovery via Adaptive Sample Reweighting
An Zhang, Fangfu Liu, Wenchang Ma et al.
Boosting Multiagent Reinforcement Learning via Permutation Invariant and Permutation Equivariant Networks
Jianye HAO, Xiaotian Hao, Hangyu Mao et al.
Boosting the Cycle Counting Power of Graph Neural Networks with I$^2$-GNNs
Yinan Huang, Xingang Peng, Jianzhu Ma et al.
Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint
Borui Zhang, Wenzhao Zheng, Jie Zhou et al.
Bounded rationality in structured density estimation
Tianyuan Teng, Kevin Li, Hang Zhang
Bounding the Family-Wise Error Rate in Local Causal Discovery Using Rademacher Averages (Extended Abstract)
Dario Simionato, Fabio Vandin
BrainBERT: Self-supervised representation learning for intracranial recordings
Christopher Wang, Vighnesh Subramaniam, Adam Uri Yaari et al.
Brain-like representational straightening of natural movies in robust feedforward neural networks
Tahereh Toosi, Elias Issa
Breaking Correlation Shift via Conditional Invariant Regularizer
Mingyang Yi, Ruoyu Wang, Jiacheng Sun et al.
Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation
Qiwen Cui, Kaiqing Zhang, Simon Du
Break It Down: Evidence for Structural Compositionality in Neural Networks
Michael Lepori, Thomas Serre, Ellie Pavlick
Bridge the Inference Gaps of Neural Processes via Expectation Maximization
Qi Wang, Marco Federici, Herke van Hoof