Papers
8,340 papers found
From Adaptive Query Release to Machine Unlearning
Enayat Ullah, Raman Arora
From Hypergraph Energy Functions to Hypergraph Neural Networks
Yuxin Wang, Quan Gan, Xipeng Qiu et al.
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning
Edwige Cyffers, Aurélien Bellet, Debabrota Basu
From Perception to Programs: Regularize, Overparameterize, and Amortize
Hao Tang, Kevin Ellis
From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks
Cai Zhou, Xiyuan Wang, Muhan Zhang
From Robustness to Privacy and Back
Hilal Asi, Jonathan Ullman, Lydia Zakynthinou
From Temporal to Contemporaneous Iterative Causal Discovery in the Presence of Latent Confounders
Raanan Yehezkel Rohekar, Shami Nisimov, Yaniv Gurwicz et al.
Fully-Adaptive Composition in Differential Privacy
Justin Whitehouse, Aaditya Ramdas, Ryan Rogers et al.
Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes
Ba-Hien Tran, Babak Shahbaba, Stephan Mandt et al.
Fully Dynamic Submodular Maximization over Matroids
Paul Duetting, Federico Fusco, Silvio Lattanzi et al.
Functional Neural Networks: Shift invariant models for functional data with applications to EEG classification
Florian Heinrichs, Mavin Heim, Corinna Weber
Function-Space Regularization in Neural Networks: A Probabilistic Perspective
Tim G. J. Rudner, Sanyam Kapoor, Shikai Qiu et al.
Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods
Aleksandr Shevchenko, Kevin Kögler, Hamed Hassani et al.
Fundamental Tradeoffs in Learning with Prior Information
Anirudha Majumdar
FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning
Songtao Liu, Zhengkai Tu, Minkai Xu et al.
Future-conditioned Unsupervised Pretraining for Decision Transformer
Zhihui Xie, Zichuan Lin, Deheng Ye et al.
GAT: Guided Adversarial Training with Pareto-optimal Auxiliary Tasks
Salah Ghamizi, Jingfeng Zhang, Maxime Cordy et al.
Gaussian processes at the Helm(holtz): A more fluid model for ocean currents
Renato Berlinghieri, Brian L. Trippe, David R. Burt et al.
Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients
Marc Harkonen, Markus Lange-Hegermann, Bogdan Raita
GC-Flow: A Graph-Based Flow Network for Effective Clustering
Tianchun Wang, Farzaneh Mirzazadeh, Xiang Zhang et al.
GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models
Hanjing Wang, Man-Kit Sit, Congjie He et al.
GeCoNeRF: Few-shot Neural Radiance Fields via Geometric Consistency
Min-Seop Kwak, Jiuhn Song, Seungryong Kim
General Covariance Data Augmentation for Neural PDE Solvers
Vladimir Fanaskov, Tianchi Yu, Alexander Rudikov et al.
Generalization Analysis for Contrastive Representation Learning
Yunwen Lei, Tianbao Yang, Yiming Ying et al.
Generalization Bounds using Data-Dependent Fractal Dimensions
Benjamin Dupuis, George Deligiannidis, Umut Simsekli