All Papers
34,598 papers found • Page 558 of 692
Conference
InterpGNN: Understand and Improve Generalization Ability of Transdutive GNNs through the Lens of Interplay between Train and Test Nodes
Jiawei Sun, Kailai Li, Ruoxin Chen et al.
Interplay of ROC and Precision-Recall AUCs: Theoretical Limits and Practical Implications in Binary Classification
Martin Mihelich, François Castagnos, Charles Dognin
Interpretability-Guided Test-Time Adversarial Defense
Akshay Ravindra Kulkarni, Tsui-Wei Weng
Interpretability Illusions in the Generalization of Simplified Models
Dan Friedman, Andrew Lampinen, Lucas Dixon et al.
Interpretable3D: An Ad
Hoc Interpretable Classifier for 3D Point Clouds - Tuo Feng, Ruijie Quan, Xiaohan Wang et al.
Interpretable Deep Clustering for Tabular Data
Jonathan Svirsky, Ofir Lindenbaum
Interpretable Diffusion via Information Decomposition
Xianghao Kong, Ollie Liu, Han Li et al.
Interpretable Measures of Conceptual Similarity by Complexity-Constrained Descriptive Auto-Encoding
Alessandro Achille, Greg Ver Steeg, Tian Yu Liu et al.
Interpretable Meta-Learning of Physical Systems
Matthieu Blanke, marc lelarge
Interpretable Sparse System Identification: Beyond Recent Deep Learning Techniques on Time-Series Prediction
Liu Xiaoyi, Duxin Chen, Wenjia Wei et al.
InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature Interpretation
Jacob Si, Wendy Yusi Cheng, Michael Cooper et al.
InterpretARA: Enhancing Hybrid Automatic Readability Assessment with Linguistic Feature Interpreter and Contrastive Learning
Jinshan Zeng, Xianchao Tong, Xianglong Yu et al.
Interpreting and Improving Diffusion Models from an Optimization Perspective
Frank Permenter, Chenyang Yuan
Interpreting and Improving Large Language Models in Arithmetic Calculation
Wei Zhang, Wan Chaoqun, Yonggang Zhang et al.
Interpreting CLIP's Image Representation via Text-Based Decomposition
Yossi Gandelsman, Alexei Efros, Jacob Steinhardt
Interpreting Equivariant Representations
Andreas Abildtrup Hansen, Anna Calissano, Aasa Feragen
Interpreting Robustness Proofs of Deep Neural Networks
Debangshu Banerjee, Avaljot Singh, Gagandeep Singh
Intersecting-Boundary-Sensitive Fingerprinting for Tampering Detection of DNN Models
Xiaofan Bai, Chaoxiang He, Xiaojing Ma et al.
Intersectional Unfairness Discovery
Gezheng Xu, Qi CHEN, Charles X. Ling et al.
Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach
Aoqi Zuo, yiqing li, Susan Wei et al.
Inter-X: Towards Versatile Human-Human Interaction Analysis
Liang Xu, Xintao Lv, Yichao Yan et al.
Intra- and Inter-group Optimal Transport for User-Oriented Fairness in Recommender Systems
Zhongxuan Han, Chaochao Chen, Xiaolin Zheng et al.
INTRA: Interaction Relationship-aware Weakly Supervised Affordance Grounding
jiha jang, Hoigi Seo, Se Young Chun
Intraoperative 2D/3D Image Registration via Differentiable X-ray Rendering
Vivek Gopalakrishnan, Neel Dey, Polina Golland
Intriguing Properties of Data Attribution on Diffusion Models
Xiaosen Zheng, Tianyu Pang, Chao Du et al.
Intriguing Properties of Diffusion Models: An Empirical Study of the Natural Attack Capability in Text-to-Image Generative Models
Takami Sato, Justin Yue, Nanze Chen et al.
Intriguing Properties of Generative Classifiers
Priyank Jaini, Kevin Clark, Robert Geirhos
Intrinsic Action Tendency Consistency for Cooperative Multi-Agent Reinforcement Learning
Junkai Zhang, Yifan Zhang, Xi Sheryl Zhang et al.
IntrinsicAnything: Learning Diffusion Priors for Inverse Rendering Under Unknown Illumination
Xi Chen, Sida Peng, Dongchen Yang et al.
IntrinsicAvatar: Physically Based Inverse Rendering of Dynamic Humans from Monocular Videos via Explicit Ray Tracing
Shaofei Wang, Bozidar Antic, Andreas Geiger et al.
Intrinsic Image Diffusion for Indoor Single-view Material Estimation
Peter Kocsis, Vincent Sitzmann, Matthias Nießner
Intrinsic Phase-Preserving Networks for Depth Super Resolution
Xuanhong Chen, Hang Wang, Jinfan Liu et al.
Intrinsic Single-Image HDR Reconstruction
Sebastian Dille, Chris Careaga, Yagiz Aksoy
Introducing Routing Functions to Vision-Language Parameter-Efficient Fine-Tuning with Low-Rank Bottlenecks
Tingyu Qu, Tinne Tuytelaars, Marie-Francine Moens
In value-based deep reinforcement learning, a pruned network is a good network
Johan Obando Ceron, Aaron Courville, Pablo Samuel Castro
Invariance-based Learning of Latent Dynamics
Kai Lagemann, Christian Lagemann, Sach Mukherjee
Invariant Random Forest: Tree-Based Model Solution for OOD Generalization
Yufan LIAO, Qi Wu, Xing Yan
Invariant Risk Minimization Is A Total Variation Model
Zhao-Rong Lai, Weiwen Wang
Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
Shida Wang, Zhong Li, Qianxiao Li
Inverse Rendering of Glossy Objects via the Neural Plenoptic Function and Radiance Fields
Haoyuan Wang, Wenbo Hu, Lei Zhu et al.
Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects
Aaron Fisher
Inverse Weight-Balancing for Deep Long-Tailed Learning
Wenqi Dang, Zhou Yang, Weisheng Dong et al.
Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image Restoration
Peyman Milanfar, Mauricio Delbracio
Inversion-Free Image Editing with Language-Guided Diffusion Models
Sihan Xu, Yidong Huang, Jiayi Pan et al.
Invertible Neural Warp for NeRF
Shin-Fang Chng, Ravi Garg, Hemanth Saratchandran et al.
Investigating and Mitigating the Side Effects of Noisy Views for Self-Supervised Clustering Algorithms in Practical Multi-View Scenarios
Jie Xu, Yazhou Ren, Xiaolong Wang et al.
Investigating Compositional Challenges in Vision-Language Models for Visual Grounding
Yunan Zeng, Yan Huang, Jinjin Zhang et al.
Investigating Pre-Training Objectives for Generalization in Vision-Based Reinforcement Learning
Donghu Kim, Hojoon Lee, Kyungmin Lee et al.
Investigating Style Similarity in Diffusion Models
Gowthami Somepalli, Anubhav Anubhav, Kamal Gupta et al.
Investigating the Benefits of Projection Head for Representation Learning
Yihao Xue, Eric Gan, Jiayi Ni et al.