Papers
8,340 papers found
Graph Neural Networks with Learnable and Optimal Polynomial Bases
Yuhe Guo, Zhewei Wei
Graph Neural Tangent Kernel: Convergence on Large Graphs
Sanjukta Krishnagopal, Luana Ruiz
Graph Positional Encoding via Random Feature Propagation
Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua et al.
Graph Reinforcement Learning for Network Control via Bi-Level Optimization
Daniele Gammelli, James Harrison, Kaidi Yang et al.
Graph Switching Dynamical Systems
Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas et al.
GREAD: Graph Neural Reaction-Diffusion Networks
Jeongwhan Choi, Seoyoung Hong, Noseong Park et al.
Great Models Think Alike: Improving Model Reliability via Inter-Model Latent Agreement
Ailin Deng, Miao Xiong, Bryan Hooi
Grounding Language Models to Images for Multimodal Inputs and Outputs
Jing Yu Koh, Ruslan Salakhutdinov, Daniel Fried
Grounding Large Language Models in Interactive Environments with Online Reinforcement Learning
Thomas Carta, Clément Romac, Thomas Wolf et al.
Group Equivariant Fourier Neural Operators for Partial Differential Equations
Jacob Helwig, Xuan Zhang, Cong Fu et al.
GuardHFL: Privacy Guardian for Heterogeneous Federated Learning
Hanxiao Chen, Meng Hao, Hongwei Li et al.
Guiding Pretraining in Reinforcement Learning with Large Language Models
Yuqing Du, Olivia Watkins, Zihan Wang et al.
Half-Hop: A graph upsampling approach for slowing down message passing
Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor et al.
Hardness of Independent Learning and Sparse Equilibrium Computation in Markov Games
Dylan J Foster, Noah Golowich, Sham M. Kakade
Hardware-Aware Compression with Random Operation Access Specific Tile (ROAST) Hashing
Aditya Desai, Keren Zhou, Anshumali Shrivastava
Harmonic Neural Networks
Atiyo Ghosh, Antonio Andrea Gentile, Mario Dagrada et al.
HarsanyiNet: Computing Accurate Shapley Values in a Single Forward Propagation
Lu Chen, Siyu Lou, Keyan Zhang et al.
HETAL: Efficient Privacy-preserving Transfer Learning with Homomorphic Encryption
Seewoo Lee, Garam Lee, Jung Woo Kim et al.
Hidden Symmetries of ReLU Networks
Elisenda Grigsby, Kathryn Lindsey, David Rolnick
Hiding Data Helps: On the Benefits of Masking for Sparse Coding
Muthu Chidambaram, Chenwei Wu, Yu Cheng et al.
Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles
Chaitanya Ryali, Yuan-Ting Hu, Daniel Bolya et al.
Hierarchical Diffusion for Offline Decision Making
Wenhao Li, Xiangfeng Wang, Bo Jin et al.
Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction
Minghao Guo, Veronika Thost, Samuel W Song et al.
Hierarchical Imitation Learning with Vector Quantized Models
Kalle Kujanpää, Joni Pajarinen, Alexander Ilin