Papers
Interpolation and Regularization for Causal Learning
Leena Chennuru Vankadara, Luca Rendsburg, Ulrike V. Luxburg et al.
Interpreting Operation Selection in Differentiable Architecture Search: A Perspective from Influence-Directed Explanations
Miao Zhang, Wei Huang, Bin Yang
Interventions, Where and How? Experimental Design for Causal Models at Scale
Panagiotis Tigas, Yashas Annadani, Andrew Jesson et al.
In the Eye of the Beholder: Robust Prediction with Causal User Modeling
Amir Feder, Guy Horowitz, Yoav Wald et al.
Intra-agent speech permits zero-shot task acquisition
Chen Yan, Federico Carnevale, Petko I Georgiev et al.
Intrinsic dimensionality estimation using Normalizing Flows
Christian Horvat, Jean-Pascal Pfister
Introspective Learning : A Two-Stage approach for Inference in Neural Networks
Mohit Prabhushankar, Ghassan AlRegib
Invariance-Aware Randomized Smoothing Certificates
Jan Schuchardt, Stephan Günnemann
Invariance Learning based on Label Hierarchy
Shoji Toyota, Kenji Fukumizu
Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations
Alexander Immer, Tycho van der Ouderaa, Gunnar Rätsch et al.
Invariant and Transportable Representations for Anti-Causal Domain Shifts
Yibo Jiang, Victor Veitch
Inverse Design for Fluid-Structure Interactions using Graph Network Simulators
Kelsey Allen, Tatiana Lopez-Guevara, Kimberly L Stachenfeld et al.
Inverse Game Theory for Stackelberg Games: the Blessing of Bounded Rationality
Jibang Wu, Weiran Shen, Fei Fang et al.
Invertible Monotone Operators for Normalizing Flows
Byeongkeun Ahn, Chiyoon Kim, Youngjoon Hong et al.
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This?
Henry Kvinge, Tegan Emerson, Grayson Jorgenson et al.
Iron: Private Inference on Transformers
Meng Hao, Hongwei Li, Hanxiao Chen et al.
Is $L^2$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network?
Chuwei Wang, Shanda Li, Di He et al.
Is a Modular Architecture Enough?
Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie
Is Integer Arithmetic Enough for Deep Learning Training?
Alireza Ghaffari, Marzieh S. Tahaei, Mohammadreza Tayaranian et al.
Iso-Dream: Isolating and Leveraging Noncontrollable Visual Dynamics in World Models
Minting Pan, Xiangming Zhu, Yunbo Wang et al.
Isometric 3D Adversarial Examples in the Physical World
yibo miao, Yinpeng Dong, Jun Zhu et al.
Is one annotation enough? - A data-centric image classification benchmark for noisy and ambiguous label estimation
Lars Schmarje, Vasco Grossmann, Claudius Zelenka et al.
Is Out-of-Distribution Detection Learnable?
Zhen Fang, Yixuan Li, Jie Lu et al.
Is Sortition Both Representative and Fair?
Soroush Ebadian, Gregory Kehne, Evi Micha et al.
Is this the Right Neighborhood? Accurate and Query Efficient Model Agnostic Explanations
Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Karthikeyan Shanmugam