Papers
8,340 papers found
Generalization on the Unseen, Logic Reasoning and Degree Curriculum
Emmanuel Abbe, Samy Bengio, Aryo Lotfi et al.
Generalized Disparate Impact for Configurable Fairness Solutions in ML
Luca Giuliani, Eleonora Misino, Michele Lombardi
Generalized Implicit Follow-The-Regularized-Leader
Keyi Chen, Francesco Orabona
Generalized Polyak Step Size for First Order Optimization with Momentum
Xiaoyu Wang, Mikael Johansson, Tong Zhang
Generalized Reductions: Making any Hierarchical Clustering Fair and Balanced with Low Cost
Marina Knittel, Max Springer, John P Dickerson et al.
Generalized-Smooth Nonconvex Optimization is As Efficient As Smooth Nonconvex Optimization
Ziyi Chen, Yi Zhou, Yingbin Liang et al.
Generalized Teacher Forcing for Learning Chaotic Dynamics
Florian Hess, Zahra Monfared, Manuel Brenner et al.
Generalizing Neural Wave Functions
Nicholas Gao, Stephan Günnemann
General Sequential Episodic Memory Model
Arjun Karuvally, Terrence Sejnowski, Hava T Siegelmann
Generated Graph Detection
Yihan Ma, Zhikun Zhang, Ning Yu et al.
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