Papers
11,015 papers found
ARTEMIS: Attention-based Retrieval with Text-Explicit Matching and Implicit Similarity
Ginger Delmas, Rafael S. Rezende, Gabriela Csurka et al.
AS-MLP: An Axial Shifted MLP Architecture for Vision
Dongze Lian, Zehao Yu, Xing Sun et al.
Assessing Generalization of SGD via Disagreement
Yiding Jiang, Vaishnavh Nagarajan, Christina Baek et al.
Associated Learning: an Alternative to End-to-End Backpropagation that Works on CNN, RNN, and Transformer
Dennis Y.H. Wu, Dinan Lin, Vincent Chen et al.
A Statistical Framework for Efficient Out of Distribution Detection in Deep Neural Networks
Matan Haroush, Tzviel Frostig, Ruth Heller et al.
Asymmetry Learning for Counterfactually-invariant Classification in OOD Tasks
S Chandra Mouli, Bruno Ribeiro
A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model
Jianwen Xie, Yaxuan Zhu, Jun Li et al.
A Theoretical Analysis on Feature Learning in Neural Networks: Emergence from Inputs and Advantage over Fixed Features
Zhenmei Shi, Junyi Wei, Yingyu Liang
A Theory of Tournament Representations
Arun Rajkumar, Vishnu Veerathu, Abdul Bakey Mir
Attacking deep networks with surrogate-based adversarial black-box methods is easy
Nicholas A. Lord, Romain Mueller, Luca Bertinetto
Attention-based Interpretability with Concept Transformers
Mattia Rigotti, Christoph Miksovic, Ioana Giurgiu et al.
Audio Lottery: Speech Recognition Made Ultra-Lightweight, Noise-Robust, and Transferable
Shaojin Ding, Tianlong Chen, Zhangyang Wang
Augmented Sliced Wasserstein Distances
Xiongjie Chen, Yongxin Yang, Yunpeng Li
A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training
Yifei Wang, Yisen Wang, Jiansheng Yang et al.
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training
Anh Tuan Bui, Trung Le, Quan Hung Tran et al.
Automated Self-Supervised Learning for Graphs
Wei Jin, Xiaorui Liu, Xiangyu Zhao et al.
Automatic Loss Function Search for Predict-Then-Optimize Problems with Strong Ranking Property
Boshi Wang, Jialin Yi, Hang Dong et al.
Autonomous Learning of Object-Centric Abstractions for High-Level Planning
Steven James, Benjamin Rosman, George Konidaris
Autonomous Reinforcement Learning: Formalism and Benchmarking
Archit Sharma, Kelvin Xu, Nikhil Sardana et al.
Autoregressive Diffusion Models
Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings et al.
Autoregressive Quantile Flows for Predictive Uncertainty Estimation
Phillip Si, Allan Bishop, Volodymyr Kuleshov
Auto-scaling Vision Transformers without Training
Wuyang Chen, Wei Huang, Xianzhi Du et al.
Auto-Transfer: Learning to Route Transferable Representations
Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss et al.
Axiomatic Explanations for Visual Search, Retrieval, and Similarity Learning
Mark Hamilton, Scott Lundberg, Stephanie Fu et al.
A Zest of LIME: Towards Architecture-Independent Model Distances
Hengrui Jia, Hongyu Chen, Jonas Guan et al.