Papers
Homomorphism AutoEncoder -- Learning Group Structured Representations from Observed Transitions
Hamza Keurti, Hsiao-Ru Pan, Michel Besserve et al.
HOPE: High-order Graph ODE For Modeling Interacting Dynamics
Xiao Luo, Jingyang Yuan, Zijie Huang et al.
Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision Processes
Runlong Zhou, Ruosong Wang, Simon Shaolei Du
How Bad is Top-$K$ Recommendation under Competing Content Creators?
Fan Yao, Chuanhao Li, Denis Nekipelov et al.
How Does Information Bottleneck Help Deep Learning?
Kenji Kawaguchi, Zhun Deng, Xu Ji et al.
How Do Transformers Learn Topic Structure: Towards a Mechanistic Understanding
Yuchen Li, Yuanzhi Li, Andrej Risteski
How Jellyfish Characterise Alternating Group Equivariant Neural Networks
Edward Pearce-Crump
How Many Perturbations Break This Model? Evaluating Robustness Beyond Adversarial Accuracy
Raphael Olivier, Bhiksha Raj
How much does Initialization Affect Generalization?
Sameera Ramasinghe, Lachlan Ewen Macdonald, Moshiur Farazi et al.
How Powerful are Shallow Neural Networks with Bandlimited Random Weights?
Ming Li, Sho Sonoda, Feilong Cao et al.
How to address monotonicity for model risk management?
Dangxing Chen, Weicheng Ye
How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Control
Jacopo Teneggi, Matthew Tivnan, Web Stayman et al.
Human-Timescale Adaptation in an Open-Ended Task Space
Jakob Bauer, Kate Baumli, Feryal Behbahani et al.
Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection
Marc Lafon, Elias Ramzi, Clément Rambour et al.
Hyena Hierarchy: Towards Larger Convolutional Language Models
Michael Poli, Stefano Massaroli, Eric Nguyen et al.
Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning
Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne et al.
Hyperbolic Image-text Representations
Karan Desai, Maximilian Nickel, Tanmay Rajpurohit et al.
Hyperbolic Representation Learning: Revisiting and Advancing
Menglin Yang, Min Zhou, Rex Ying et al.
Hyperparameters in Reinforcement Learning and How To Tune Them
Theresa Eimer, Marius Lindauer, Roberta Raileanu
HyperTuning: Toward Adapting Large Language Models without Back-propagation
Jason Phang, Yi Mao, Pengcheng He et al.
Hypervolume Knowledge Gradient: A Lookahead Approach for Multi-Objective Bayesian Optimization with Partial Information
Sam Daulton, Maximilian Balandat, Eytan Bakshy
Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds through Algorithmic Stability
Anass Aghbalou, Guillaume Staerman
I$^2$SB: Image-to-Image Schrödinger Bridge
Guan-Horng Liu, Arash Vahdat, De-An Huang et al.
Identifiability and Generalizability in Constrained Inverse Reinforcement Learning
Andreas Schlaginhaufen, Maryam Kamgarpour