Papers
8,340 papers found
Inferring Relational Potentials in Interacting Systems
Armand Comas, Yilun Du, Christian Fernandez Lopez et al.
Infinite Action Contextual Bandits with Reusable Data Exhaust
Mark Rucker, Yinglun Zhu, Paul Mineiro
Inflow, Outflow, and Reciprocity in Machine Learning
Mukund Sundararajan, Walid Krichene
InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models
Yingheng Wang, Yair Schiff, Aaron Gokaslan et al.
InfoOT: Information Maximizing Optimal Transport
Ching-Yao Chuang, Stefanie Jegelka, David Alvarez-Melis
Information-Theoretic State Space Model for Multi-View Reinforcement Learning
Hyeongjoo Hwang, Seokin Seo, Youngsoo Jang et al.
Infusing Lattice Symmetry Priors in Attention Mechanisms for Sample-Efficient Abstract Geometric Reasoning
Mattia Atzeni, Mrinmaya Sachan, Andreas Loukas
InGram: Inductive Knowledge Graph Embedding via Relation Graphs
Jaejun Lee, Chanyoung Chung, Joyce Jiyoung Whang
In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation
Julian Bitterwolf, Maximilian Müller, Matthias Hein
Input Perturbation Reduces Exposure Bias in Diffusion Models
Mang Ning, Enver Sangineto, Angelo Porrello et al.
Input uncertainty propagation through trained neural networks
Paul Monchot, Loic Coquelin, Sébastien Julien Petit et al.
In Search for a Generalizable Method for Source Free Domain Adaptation
Malik Boudiaf, Tom Denton, Bart Van Merrienboer et al.
In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect Estimation
Alicia Curth, Mihaela Van Der Schaar
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models
Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen et al.
Instrumental Variable Estimation of Average Partial Causal Effects
Yuta Kawakami, Manabu Kuroki, Jin Tian
Integrating Prior Knowledge in Contrastive Learning with Kernel
Benoit Dufumier, Carlo Alberto Barbano, Robin Louiset et al.
Interactive Object Placement with Reinforcement Learning
Shengping Zhang, Quanling Meng, Qinglin Liu et al.
Internally Rewarded Reinforcement Learning
Mengdi Li, Xufeng Zhao, Jae Hee Lee et al.
Internet Explorer: Targeted Representation Learning on the Open Web
Alexander Cong Li, Ellis Langham Brown, Alexei A Efros et al.
Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics
Jiacheng Zhu, Jielin Qiu, Aritra Guha et al.
Interpretable Neural-Symbolic Concept Reasoning
Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini et al.
Interval Bound Interpolation for Few-shot Learning with Few Tasks
Shounak Datta, Sankha Subhra Mullick, Anish Chakrabarty et al.
Interventional Causal Representation Learning
Kartik Ahuja, Divyat Mahajan, Yixin Wang et al.
Intrinsic Sliced Wasserstein Distances for Comparing Collections of Probability Distributions on Manifolds and Graphs
Raif M. Rustamov, Subhabrata Majumdar
Invariance in Policy Optimisation and Partial Identifiability in Reward Learning
Joar Max Viktor Skalse, Matthew Farrugia-Roberts, Stuart Russell et al.