Papers
Improving N-Glycosylation and Biopharmaceutical Production Predictions Using AutoML-Built Residual Hybrid Models
Pedro Seber, Richard Braatz
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization
Deep Chakraborty, Yann LeCun, Tim G. J. Rudner et al.
Improving Stochastic Cubic Newton with Momentum
El Mahdi Chayti, Nikita Doikov, Martin Jaggi
Incremental Uncertainty-aware Performance Monitoring with Active Labeling Intervention
Alexander Koebler, Thomas Decker, Ingo Thon et al.
Independent Learning in Performative Markov Potential Games
Rilind Sahitaj, Paulius Sasnauskas, Yiğit Yalın et al.
Infinite-dimensional Diffusion Bridge Simulation via Operator Learning
Gefan Yang, Elizabeth Louise Baker, Michael Lind Severinsen et al.
Infinite-Horizon Reinforcement Learning with Multinomial Logit Function Approximation
Jaehyun Park, Junyeop Kwon, Dabeen Lee
Infinite Width Limits of Self Supervised Neural Networks
Maximilian Fleissner, Gautham Govind Anil, Debarghya Ghoshdastidar
InfoNCE: Identifying the Gap Between Theory and Practice
Evgenia Rusak, Patrik Reizinger, Attila Juhos et al.
Information-Theoretic Causal Discovery in Topological Order
Sascha Xu, Sarah Mameche, Jilles Vreeken
Information-Theoretic Measures on Lattices for Higher-Order Interactions
Zhaolu Liu, Mauricio Barahona, Robert Peach
Information Transfer Across Clinical Tasks via Adaptive Parameter Optimisation
Anshul Thakur, Elena Gal, Soheila Molaei et al.
InnerThoughts: Disentangling Representations and Predictions in Large Language Models
Didier Chételat, Joseph Cotnareanu, Rylee Thompson et al.
Integer Programming Based Methods and Heuristics for Causal Graph Learning
Sanjeeb Dash, Joao Goncalves, Tian Gao
Invariant Link Selector for Spatial-Temporal Out-of-Distribution Problem
Katherine Tieu, Dongqi Fu, Jun Wu et al.
Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems
Da Long, Zhitong Xu, Qiwei Yuan et al.
Is Gibbs sampling faster than Hamiltonian Monte Carlo on GLMs?
Son Luu, Zuheng Xu, Nikola Surjanovic et al.
Is Merging Worth It? Securely Evaluating the Information Gain for Causal Dataset Acquisition
Jake Fawkes, Lucile Ter-Minassian, Desi R. Ivanova et al.
Is Prior-Free Black-Box Non-Stationary Reinforcement Learning Feasible?
Argyrios Gerogiannis, Yu-Han Huang, Venugopal Veeravalli
I-trustworthy Models. A framework for trustworthiness evaluation of probabilistic classifiers
Ritwik Vashistha, Arya Farahi
Keeping up with dynamic attackers: Certifying robustness to adaptive online data poisoning
Avinandan Bose, Laurent Lessard, Maryam Fazel et al.
Kernel Single Proxy Control for Deterministic Confounding
Liyuan Xu, Arthur Gretton
Knowledge Graph Completion with Mixed Geometry Tensor Factorization
Viacheslav Yusupov, Maxim Rakhuba, Evgeny Frolov
Koopman-Equivariant Gaussian Processes
Petar Bevanda, Max Beier, Alexandre Capone et al.