Papers
11,015 papers found
Any-scale Balanced Samplers for Discrete Space
Haoran Sun, Bo Dai, Charles Sutton et al.
Approximate Bayesian Inference with Stein Functional Variational Gradient Descent
Tobias Pielok, Bernd Bischl, David Rügamer
Approximate Nearest Neighbor Search through Modern Error-Correcting Codes
Noam Touitou, Nissim Halabi
Approximate Vanishing Ideal Computations at Scale
Elias Samuel Wirth, Hiroshi Kera, Sebastian Pokutta
Approximation and non-parametric estimation of functions over high-dimensional spheres via deep ReLU networks
Namjoon Suh, Tian-Yi Zhou, Xiaoming Huo
A Primal-Dual Framework for Transformers and Neural Networks
Tan Minh Nguyen, Tam Minh Nguyen, Nhat Ho et al.
A probabilistic framework for task-aligned intra- and inter-area neural manifold estimation
Edoardo Balzani, Jean-Paul G Noel, Pedro Herrero-Vidal et al.
Arbitrary Virtual Try-on Network: Characteristics Representation and Trade-off between Body and Clothing
Yu Liu, Mingbo Zhao, Zhao Zhang et al.
ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations
Xuyang Zhao, Tianqi Du, Yisen Wang et al.
Are More Layers Beneficial to Graph Transformers?
Haiteng Zhao, Shuming Ma, Dongdong Zhang et al.
Artificial Neuronal Ensembles with Learned Context Dependent Gating
Matthew James Tilley, Michelle Miller, David Freedman
A Self-Attention Ansatz for Ab-initio Quantum Chemistry
Ingrid von Glehn, James S Spencer, David Pfau
A Simple Approach for Visual Room Rearrangement: 3D Mapping and Semantic Search
Brandon Trabucco, Gunnar A Sigurdsson, Robinson Piramuthu et al.
A Simple Yet Powerful Deep Active Learning With Snapshots Ensembles
Seohyeon Jung, Sanghyun Kim, Juho Lee
Ask Me Anything: A simple strategy for prompting language models
Simran Arora, Avanika Narayan, Mayee F Chen et al.
Associative Memory Augmented Asynchronous Spatiotemporal Representation Learning for Event-based Perception
Uday Kamal, Saurabh Dash, Saibal Mukhopadhyay
A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks
Marc Anton Finzi, Andres Potapczynski, Matthew Choptuik et al.
A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy
Kaan Ozkara, Antonious M. Girgis, Deepesh Data et al.
Asymptotic Instance-Optimal Algorithms for Interactive Decision Making
Kefan Dong, Tengyu Ma
Asynchronous Distributed Bilevel Optimization
Yang Jiao, Kai Yang, Tiancheng Wu et al.
Asynchronous Gradient Play in Zero-Sum Multi-agent Games
Ruicheng Ao, Shicong Cen, Yuejie Chi
A System for Morphology-Task Generalization via Unified Representation and Behavior Distillation
Hiroki Furuta, Yusuke Iwasawa, Yutaka Matsuo et al.
A Theoretical Framework for Inference and Learning in Predictive Coding Networks
Beren Millidge, Yuhang Song, Tommaso Salvatori et al.
A theoretical study of inductive biases in contrastive learning
Jeff Z. HaoChen, Tengyu Ma
A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity
Hongkang Li, Meng Wang, Sijia Liu et al.