Papers
11,015 papers found
Generalized Energy Based Models
Michael Arbel, Liang Zhou, Arthur Gretton
Generalized Multimodal ELBO
Thomas M. Sutter, Imant Daunhawer, Julia E Vogt
Generalized Variational Continual Learning
Noel Loo, Siddharth Swaroop, Richard E Turner
Generating Adversarial Computer Programs using Optimized Obfuscations
Shashank Srikant, Sijia Liu, Tamara Mitrovska et al.
Generating Furry Cars: Disentangling Object Shape and Appearance across Multiple Domains
Utkarsh Ojha, Krishna Kumar Singh, Yong Jae Lee
Generative Language-Grounded Policy in Vision-and-Language Navigation with Bayes' Rule
Shuhei Kurita, Kyunghyun Cho
Generative Scene Graph Networks
Fei Deng, Zhuo Zhi, Donghun Lee et al.
Generative Time-series Modeling with Fourier Flows
Ahmed Alaa, Alex James Chan, Mihaela van der Schaar
Genetic Soft Updates for Policy Evolution in Deep Reinforcement Learning
Enrico Marchesini, Davide Corsi, Alessandro Farinelli
Geometry-Aware Gradient Algorithms for Neural Architecture Search
Liam Li, Mikhail Khodak, Nina Balcan et al.
Geometry-aware Instance-reweighted Adversarial Training
Jingfeng Zhang, Jianing Zhu, Gang Niu et al.
Getting a CLUE: A Method for Explaining Uncertainty Estimates
Javier Antoran, Umang Bhatt, Tameem Adel et al.
Global Convergence of Three-layer Neural Networks in the Mean Field Regime
Huy Tuan Pham, Phan-Minh Nguyen
Go with the flow: Adaptive control for Neural ODEs
Mathieu Chalvidal, Matthew Ricci, Rufin VanRullen et al.
Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability
Jeremy Cohen, Simran Kaur, Yuanzhi Li et al.
Gradient Origin Networks
Sam Bond-Taylor, Chris G. Willcocks
Gradient Projection Memory for Continual Learning
Gobinda Saha, Isha Garg, Kaushik Roy
Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models
Zirui Wang, Yulia Tsvetkov, Orhan Firat et al.
gradSim: Differentiable simulation for system identification and visuomotor control
J. Krishna Murthy, Miles Macklin, Florian Golemo et al.
Graph-Based Continual Learning
Binh Tang, David S. Matteson
Graph Coarsening with Neural Networks
Chen Cai, Dingkang Wang, Yusu Wang
GraphCodeBERT: Pre-training Code Representations with Data Flow
Daya Guo, Shuo Ren, Shuai Lu et al.
Graph Convolution with Low-rank Learnable Local Filters
Xiuyuan Cheng, Zichen Miao, Qiang Qiu
Graph Edit Networks
Benjamin Paassen, Daniele Grattarola, Daniele Zambon et al.