Papers
Improving Adversarial Robustness Through the Contrastive-Guided Diffusion Process
Yidong Ouyang, Liyan Xie, Guang Cheng
Improving Expert Predictions with Conformal Prediction
Eleni Straitouri, Lequn Wang, Nastaran Okati et al.
Improving Fair Training under Correlation Shifts
Yuji Roh, Kangwook Lee, Steven Euijong Whang et al.
Improving Graph Generation by Restricting Graph Bandwidth
Nathaniel Lee Diamant, Alex M Tseng, Kangway V. Chuang et al.
Improving Graph Neural Networks with Learnable Propagation Operators
Moshe Eliasof, Lars Ruthotto, Eran Treister
Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models
Rui Li, S. T. John, Arno Solin
Improving l1-Certified Robustness via Randomized Smoothing by Leveraging Box Constraints
Vaclav Voracek, Matthias Hein
Improving Medical Predictions by Irregular Multimodal Electronic Health Records Modeling
Xinlu Zhang, Shiyang Li, Zhiyu Chen et al.
Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models
Matthew J. Muckley, Alaaeldin El-Nouby, Karen Ullrich et al.
Improving the Model Consistency of Decentralized Federated Learning
Yifan Shi, Li Shen, Kang Wei et al.
Improving Visual Prompt Tuning for Self-supervised Vision Transformers
Seungryong Yoo, Eunji Kim, Dahuin Jung et al.
IncDSI: Incrementally Updatable Document Retrieval
Varsha Kishore, Chao Wan, Justin Lovelace et al.
Individually Fair Learning with One-Sided Feedback
Yahav Bechavod, Aaron Roth
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.