Papers
Generating Language Corrections for Teaching Physical Control Tasks
Megha Srivastava, Noah Goodman, Dorsa Sadigh
Generating Novel, Designable, and Diverse Protein Structures by Equivariantly Diffusing Oriented Residue Clouds
Yeqing Lin, Mohammed Alquraishi
Generating Private Synthetic Data with Genetic Algorithms
Terrance Liu, Jingwu Tang, Giuseppe Vietri et al.
Generative Adversarial Symmetry Discovery
Jianke Yang, Robin Walters, Nima Dehmamy et al.
Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting
Shayan Shirahmad Gale Bagi, Zahra Gharaee, Oliver Schulte et al.
Generative Decoding of Visual Stimuli
Eleni Miliotou, Panagiotis Kyriakis, Jason D Hinman et al.
Generative Graph Dictionary Learning
Zhichen Zeng, Ruike Zhu, Yinglong Xia et al.
Generative Pretraining for Black-Box Optimization
Satvik Mehul Mashkaria, Siddarth Krishnamoorthy, Aditya Grover
Geometric Autoencoders - What You See is What You Decode
Philipp Nazari, Sebastian Damrich, Fred A Hamprecht
Geometric Clifford Algebra Networks
David Ruhe, Jayesh K Gupta, Steven De Keninck et al.
Geometric Latent Diffusion Models for 3D Molecule Generation
Minkai Xu, Alexander S Powers, Ron O. Dror et al.
GFlowNet-EM for Learning Compositional Latent Variable Models
Edward J Hu, Nikolay Malkin, Moksh Jain et al.
GFlowOut: Dropout with Generative Flow Networks
Dianbo Liu, Moksh Jain, Bonaventure F. P. Dossou et al.
GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration
Naoki Murata, Koichi Saito, Chieh-Hsin Lai et al.
Gibbsian Polar Slice Sampling
Philip Schär, Michael Habeck, Daniel Rudolf
Git-Theta: A Git Extension for Collaborative Development of Machine Learning Models
Nikhil Kandpal, Brian Lester, Mohammed Muqeeth et al.
Global Context Vision Transformers
Ali Hatamizadeh, Hongxu Yin, Greg Heinrich et al.
Global optimality for Euclidean CCCP under Riemannian convexity
Melanie Weber, Suvrit Sra
Global optimality of Elman-type RNNs in the mean-field regime
Andrea Agazzi, Jianfeng Lu, Sayan Mukherjee
Global Optimization with Parametric Function Approximation
Chong Liu, Yu-Xiang Wang
Global Selection of Contrastive Batches via Optimization on Sample Permutations
Vin Sachidananda, Ziyi Yang, Chenguang Zhu
GLOBE-CE: A Translation Based Approach for Global Counterfactual Explanations
Dan Ley, Saumitra Mishra, Daniele Magazzeni
GNN&GBDT-Guided Fast Optimizing Framework for Large-scale Integer Programming
Huigen Ye, Hua Xu, Hongyan Wang et al.
GNOT: A General Neural Operator Transformer for Operator Learning
Zhongkai Hao, Zhengyi Wang, Hang Su et al.
GOAT: A Global Transformer on Large-scale Graphs
Kezhi Kong, Jiuhai Chen, John Kirchenbauer et al.