Papers
Generalized Doubly Reparameterized Gradient Estimators
Matthias Bauer, Andriy Mnih
Generating images with sparse representations
Charlie Nash, Jacob Menick, Sander Dieleman et al.
Generative Adversarial Networks for Markovian Temporal Dynamics: Stochastic Continuous Data Generation
Sung Woo Park, Dong Wook Shu, Junseok Kwon
Generative Adversarial Transformers
Drew A Hudson, Larry Zitnick
Generative Causal Explanations for Graph Neural Networks
Wanyu Lin, Hao Lan, Baochun Li
Generative Particle Variational Inference via Estimation of Functional Gradients
Neale Ratzlaff, Qinxun Bai, Li Fuxin et al.
Generative Video Transformer: Can Objects be the Words?
Yi-Fu Wu, Jaesik Yoon, Sungjin Ahn
GeomCA: Geometric Evaluation of Data Representations
Petra Poklukar, Anastasiia Varava, Danica Kragic
Geometric convergence of elliptical slice sampling
Viacheslav Natarovskii, Daniel Rudolf, Björn Sprungk
Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances
Berfin Simsek, François Ged, Arthur Jacot et al.
Global Convergence of Policy Gradient for Linear-Quadratic Mean-Field Control/Game in Continuous Time
Weichen Wang, Jiequn Han, Zhuoran Yang et al.
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes
Sebastian W Ober, Laurence Aitchison
Globally-Robust Neural Networks
Klas Leino, Zifan Wang, Matt Fredrikson
Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex Programs
Tolga Ergen, Mert Pilanci
Global Prosody Style Transfer Without Text Transcriptions
Kaizhi Qian, Yang Zhang, Shiyu Chang et al.
GLSearch: Maximum Common Subgraph Detection via Learning to Search
Yunsheng Bai, Derek Xu, Yizhou Sun et al.
GMAC: A Distributional Perspective on Actor-Critic Framework
Daniel W Nam, Younghoon Kim, Chan Y Park
GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings
Matthias Fey, Jan E. Lenssen, Frank Weichert et al.
Goal-Conditioned Reinforcement Learning with Imagined Subgoals
Elliot Chane-Sane, Cordelia Schmid, Ivan Laptev
GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning
Idan Achituve, Aviv Navon, Yochai Yemini et al.
Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix
Maximilian Lam, Gu-Yeon Wei, David Brooks et al.
GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training
Krishnateja Killamsetty, Durga S, Ganesh Ramakrishnan et al.
Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech
Vadim Popov, Ivan Vovk, Vladimir Gogoryan et al.
GRAND: Graph Neural Diffusion
Ben Chamberlain, James Rowbottom, Maria I Gorinova et al.
Graph Contrastive Learning Automated
Yuning You, Tianlong Chen, Yang Shen et al.