Papers
Gradient-based Adaptive Markov Chain Monte Carlo
Michalis Titsias, Petros Dellaportas
Gradient based sample selection for online continual learning
Rahaf Aljundi, Min Lin, Baptiste Goujaud et al.
Gradient Dynamics of Shallow Univariate ReLU Networks
Francis Williams, Matthew Trager, Daniele Panozzo et al.
Gradient Information for Representation and Modeling
Jie Ding, Robert Calderbank, Vahid Tarokh
Graph Agreement Models for Semi-Supervised Learning
Otilia Stretcu, Krishnamurthy Viswanathan, Dana Movshovitz-Attias et al.
Graph-based Discriminators: Sample Complexity and Expressiveness
Roi Livni, Yishay Mansour
Graph-Based Semi-Supervised Learning with Non-ignorable Non-response
Fan Zhou, Tengfei Li, Haibo Zhou et al.
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels
Simon S Du, Kangcheng Hou, Ruslan Salakhutdinov et al.
Graph Normalizing Flows
Jenny Liu, Aviral Kumar, Jimmy Ba et al.
Graph Structured Prediction Energy Networks
Colin Graber, Alexander Schwing
Graph Transformer Networks
Seongjun Yun, Minbyul Jeong, Raehyun Kim et al.
Greedy Sampling for Approximate Clustering in the Presence of Outliers
Aditya Bhaskara, Sharvaree Vadgama, Hong Xu
Grid Saliency for Context Explanations of Semantic Segmentation
Lukas Hoyer, Mauricio Munoz, Prateek Katiyar et al.
Group Retention when Using Machine Learning in Sequential Decision Making: the Interplay between User Dynamics and Fairness
Xueru Zhang, Mohammadmahdi Khaliligarekani, Cem Tekin et al.
GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series
Edward De Brouwer, Jaak Simm, Adam Arany et al.
Guided Meta-Policy Search
Russell Mendonca, Abhishek Gupta, Rosen Kralev et al.
Guided Similarity Separation for Image Retrieval
Chundi Liu, Guangwei Yu, Maksims Volkovs et al.
Hamiltonian descent for composite objectives
Brendan O'Donoghue, Chris J. Maddison
Hamiltonian Neural Networks
Samuel Greydanus, Misko Dzamba, Jason Yosinski
Handling correlated and repeated measurements with the smoothed multivariate square-root Lasso
Quentin Bertrand, Mathurin Massias, Alexandre Gramfort et al.
Heterogeneous Graph Learning for Visual Commonsense Reasoning
Weijiang Yu, Jingwen Zhou, Weihao Yu et al.
Hierarchical Decision Making by Generating and Following Natural Language Instructions
Hengyuan Hu, Denis Yarats, Qucheng Gong et al.
Hierarchical Optimal Transport for Document Representation
Mikhail Yurochkin, Sebastian Claici, Edward Chien et al.
Hierarchical Optimal Transport for Multimodal Distribution Alignment
John Lee, Max Dabagia, Eva Dyer et al.
Hierarchical Reinforcement Learning with Advantage-Based Auxiliary Rewards
Siyuan Li, Rui Wang, Minxue Tang et al.