Papers
11,955 papers found
Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model
Karsten Roth, Lukas Thede, A. Sophia Koepke et al.
Fantastic Generalization Measures are Nowhere to be Found
Michael Gastpar, Ido Nachum, Jonathan Shafer et al.
Fast and unified path gradient estimators for normalizing flows
Lorenz Vaitl, Ludwig Winkler, Lorenz Richter et al.
Fast Context-Based Low-Light Image Enhancement via Neural Implicit Representations
Tomáš Chobola, Yu Liu, Hanyi Zhang et al.
Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature
Guangsheng Bao, Yanbin Zhao, Zhiyang Teng et al.
Fast Diffusion-Based Counterfactuals for Shortcut Removal and Generation
Nina Weng, Paraskevas Pegios, Eike Petersen et al.
Fast-ELECTRA for Efficient Pre-training
Chengyu Dong, Liyuan Liu, Hao Cheng et al.
Fast Ensembling with Diffusion Schrödinger Bridge
Hyunsu Kim, Jongmin Yoon, Juho Lee
Fast Equilibrium of SGD in Generic Situations
Zhiyuan Li, Yi Wang, Zhiren Wang
Faster Approximation of Probabilistic and Distributional Values via Least Squares
Weida Li, Yaoliang Yu
Faster Sampling from Log-Concave Densities over Polytopes via Efficient Linear Solvers
Oren Mangoubi, Nisheeth K. Vishnoi
FasterViT: Fast Vision Transformers with Hierarchical Attention
Ali Hatamizadeh, Greg Heinrich, Hongxu Yin et al.
Fast, Expressive $\mathrm{SE}(n)$ Equivariant Networks through Weight-Sharing in Position-Orientation Space
Erik J Bekkers, Sharvaree Vadgama, Rob Hesselink et al.
Fast Hyperboloid Decision Tree Algorithms
Philippe Chlenski, Ethan Turok, Antonio Khalil Moretti et al.
Fast Imitation via Behavior Foundation Models
Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati et al.
Fast Training of Diffusion Transformer with Extreme Masking for 3D Point Clouds Generation
Shentong Mo, Enze Xie, Yue Wu et al.
Fast Updating Truncated SVD for Representation Learning with Sparse Matrices
Haoran Deng, Yang Yang, Jiahe Li et al.
Fast Value Tracking for Deep Reinforcement Learning
Frank Shih, Faming Liang
FeatUp: A Model-Agnostic Framework for Features at Any Resolution
Stephanie Fu, Mark Hamilton, Laura E. Brandt et al.
Feature-aligned N-BEATS with Sinkhorn divergence
Joonhun Lee, Myeongho Jeon, Myungjoo Kang et al.
Feature Collapse
Thomas Laurent, James von Brecht, Xavier Bresson
Feature emergence via margin maximization: case studies in algebraic tasks
Depen Morwani, Benjamin L. Edelman, Costin-Andrei Oncescu et al.
FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation
Haozhao Wang, Haoran Xu, Yichen Li et al.
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler
Zilinghan Li, Pranshu Chaturvedi, Shilan He et al.
FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization
Junyi Li, Feihu Huang, Heng Huang