Papers
Expectation-Complete Graph Representations with Homomorphisms
Pascal Welke, Maximilian Thiessen, Fabian Jogl et al.
Expected Gradients of Maxout Networks and Consequences to Parameter Initialization
Hanna Tseran, Guido Montufar
Expertise Trees Resolve Knowledge Limitations in Collective Decision-Making
Axel Abels, Tom Lenaerts, Vito Trianni et al.
Exphormer: Sparse Transformers for Graphs
Hamed Shirzad, Ameya Velingker, Balaji Venkatachalam et al.
Explainability as statistical inference
Hugo Henri Joseph Senetaire, Damien Garreau, Jes Frellsen et al.
Explainable Data-Driven Optimization: From Context to Decision and Back Again
Alexandre Forel, Axel Parmentier, Thibaut Vidal
Explaining Reinforcement Learning with Shapley Values
Daniel Beechey, Thomas M. S. Smith, Özgür Şimşek
Explaining the effects of non-convergent MCMC in the training of Energy-Based Models
Elisabeth Agoritsas, Giovanni Catania, Aurélien Decelle et al.
Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization
Yimeng Chen, Tianyang Hu, Fengwei Zhou et al.
Exploring Chemical Space with Score-based Out-of-distribution Generation
Seul Lee, Jaehyeong Jo, Sung Ju Hwang
Exploring Model Dynamics for Accumulative Poisoning Discovery
Jianing Zhu, Xiawei Guo, Jiangchao Yao et al.
Exploring the Benefits of Training Expert Language Models over Instruction Tuning
Joel Jang, Seungone Kim, Seonghyeon Ye et al.
Exploring the Limits of Model-Targeted Indiscriminate Data Poisoning Attacks
Yiwei Lu, Gautam Kamath, Yaoliang Yu
Exponential Smoothing for Off-Policy Learning
Imad Aouali, Victor-Emmanuel Brunel, David Rohde et al.
Extending Conformal Prediction to Hidden Markov Models with Exact Validity via de Finetti’s Theorem for Markov Chains
Buddhika Nettasinghe, Samrat Chatterjee, Ramakrishna Tipireddy et al.
Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms
Francesco Tonin, Alex Lambert, Panagiotis Patrinos et al.
Extrapolated Random Tree for Regression
Yuchao Cai, Yuheng Ma, Yiwei Dong et al.
Extrapolative Controlled Sequence Generation via Iterative Refinement
Vishakh Padmakumar, Richard Yuanzhe Pang, He He et al.
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels
Guillaume Staerman, Cédric Allain, Alexandre Gramfort et al.
FAENet: Frame Averaging Equivariant GNN for Materials Modeling
Alexandre Agm Duval, Victor Schmidt, Alex Hernández-Garcı́a et al.
Fair and Accurate Decision Making through Group-Aware Learning
Ramtin Hosseini, Li Zhang, Bhanu Garg et al.
Fair and Optimal Classification via Post-Processing
Ruicheng Xian, Lang Yin, Han Zhao
Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy Learning
Kwangho Kim, Jose R Zubizarreta