Papers
GNeSF: Generalizable Neural Semantic Fields
Hanlin Chen, Chen Li, Mengqi Guo et al.
GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels
Xin Zheng, Miao Zhang, Chunyang Chen et al.
Goal-conditioned Offline Planning from Curious Exploration
Marco Bagatella, Georg Martius
Goal-Conditioned Predictive Coding for Offline Reinforcement Learning
Zilai Zeng, Ce Zhang, Shijie Wang et al.
Goal Driven Discovery of Distributional Differences via Language Descriptions
Ruiqi Zhong, Peter Zhang, Steve Li et al.
Going Beyond Linear Mode Connectivity: The Layerwise Linear Feature Connectivity
Zhanpeng Zhou, Yongyi Yang, Xiaojiang Yang et al.
Going beyond persistent homology using persistent homology
Johanna Immonen, Amauri Souza, Vikas Garg
Gold-YOLO: Efficient Object Detector via Gather-and-Distribute Mechanism
Chengcheng Wang, Wei He, Ying Nie et al.
GPEX, A Framework For Interpreting Artificial Neural Networks
Amir Hossein Hosseini Akbarnejad, Gilbert Bigras, Nilanjan Ray
GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction
Rui Yang, Lin Song, Yanwei Li et al.
GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks
Zhonghang Li, Lianghao Xia, Yong Xu et al.
Gradient-Based Feature Learning under Structured Data
Alireza Mousavi-Hosseini, Denny Wu, Taiji Suzuki et al.
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy
Anastasiia Koloskova, Ryan McKenna, Zachary Charles et al.
Gradient-Free Kernel Stein Discrepancy
Matthew Fisher, Chris J Oates
Gradient Informed Proximal Policy Optimization
Sanghyun Son, Laura Zheng, Ryan Sullivan et al.
GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients
Sima Behpour, Thang Long Doan, Xin Li et al.
Grammar Prompting for Domain-Specific Language Generation with Large Language Models
Bailin Wang, Zi Wang, Xuezhi Wang et al.
GRAND-SLAMIN’ Interpretable Additive Modeling with Structural Constraints
Shibal Ibrahim, Gabriel Afriat, Kayhan Behdin et al.
GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph
Xin Li, Dongze Lian, Zhihe Lu et al.
Graph Contrastive Learning with Stable and Scalable Spectral Encoding
Deyu Bo, Yuan Fang, Yang Liu et al.
Graph Convolutional Kernel Machine versus Graph Convolutional Networks
Zhihao Wu, Zhao Zhang, Jicong Fan
Graph Denoising Diffusion for Inverse Protein Folding
Kai Yi, Bingxin Zhou, Yiqing Shen et al.
Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling
Haotao Wang, Ziyu Jiang, Yuning You et al.