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| 2025 | Explaining ViTs Using Information Flow. Chase Walker, Md Rubel Ahmed, Sumit Kumar Jha, Rickard Ewetz |
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| 2025 | Factor Analysis with Correlated Topic Model for Multi-Modal Data. Malgorzata Lazecka, Ewa Szczurek |
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| 2025 | Fairness Risks for Group-Conditionally Missing Demographics. Kaiqi Jiang, Wenzhe Fan, Mao Li, Xinhua Zhang |
| 2025 | Fast Convergence of Softmax Policy Mirror Ascent. Reza Asad, Reza Babanezhad Harikandeh, Issam H. Laradji, Nicolas Le Roux, Sharan Vaswani |
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| 2025 | Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-Analysis. Rémi Khellaf, Aurélien Bellet, Julie Josse |
| 2025 | Federated Communication-Efficient Multi-Objective Optimization. Baris Askin, Pranay Sharma, Gauri Joshi, Carlee Joe-Wong |
| 2025 | Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents. Safwan Labbi, Daniil Tiapkin, Lorenzo Mancini, Paul Mangold, Eric Moulines |
| 2025 | Fine-Tuning with Uncertainty-Aware Priors Makes Vision and Language Foundation Models More Reliable. Tim G. J. Rudner, Xiang Pan, Yucen Lily Li, Ravid Shwartz-Ziv, Andrew Gordon Wilson |
| 2025 | Fixed-Budget Change Point Identification in Piecewise Constant Bandits. Joseph Lazzaro, Ciara Pike-Burke |
| 2025 | Flexible Copula-Based Mixed Models in Deep Learning: A Scalable Approach to Arbitrary Marginals. Giora Simchoni, Saharon Rosset |
| 2025 | Flexible and Efficient Probabilistic PDE Solvers through Gaussian Markov Random Fields. Tim Weiland, Marvin Pförtner, Philipp Hennig |
| 2025 | Fourier Circuits in Neural Networks and Transformers: A Case Study of Modular Arithmetic with Multiple Inputs. Chenyang Li, Yingyu Liang, Zhenmei Shi, Zhao Song, Tianyi Zhou |
| 2025 | FreqMoE: Enhancing Time Series Forecasting through Frequency Decomposition Mixture of Experts. Ziqi Liu |
| 2025 | From Deep Additive Kernel Learning to Last-Layer Bayesian Neural Networks via Induced Prior Approximation. Wenyuan Zhao, Haoyuan Chen, Tie Liu, Rui Tuo, Chao Tian |
| 2025 | From Gradient Clipping to Normalization for Heavy Tailed SGD. Florian Hübler, Ilyas Fatkhullin, Niao He |
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| 2025 | Fully Dynamic Adversarially Robust Correlation Clustering in Polylogarithmic Update Time. Vladimir Braverman, Prathamesh Dharangutte, Shreyas Pai, Vihan Shah, Chen Wang |
| 2025 | Function-Space MCMC for Bayesian Wide Neural Networks. Lucia Pezzetti, Stefano Favaro, Stefano Peluchetti |
| 2025 | Functional Stochastic Gradient MCMC for Bayesian Neural Networks. Mengjing Wu, Junyu Xuan, Jie Lu |
| 2025 | Fundamental Limits of Perfect Concept Erasure. Somnath Basu Roy Chowdhury, Kumar Avinava Dubey, Ahmad Beirami, Rahul Kidambi, Nicholas Monath, Amr Ahmed, Snigdha Chaturvedi |
| 2025 | Fundamental computational limits of weak learnability in high-dimensional multi-index models. Emanuele Troiani, Yatin Dandi, Leonardo Defilippis, Lenka Zdeborová, Bruno Loureiro, Florent Krzakala |
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| 2025 | Gaussian Mean Testing under Truncation. Clément Louis Canonne, Themis Gouleakis, Yuhao Wang, Joy Qiping Yang |
| 2025 | Gaussian Smoothing in Saliency Maps: The Stability-Fidelity Trade-Off in Neural Network Interpretability. Zhuorui Ye, Farzan Farnia |
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| 2025 | Global Ground Metric Learning with Applications to scRNA data. Damin Kühn, Michael T. Schaub |
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| 2025 | Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects. Seyedeh Baharan Khatami, Harsh Parikh, Haowei Chen, Sudeepa Roy, Babak Salimi |
| 2025 | Graph-based Complexity for Causal Effect by Empirical Plug-in. Rina Dechter, Anna Raichev, Jin Tian, Alexander Ihler |
| 2025 | HACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing Risks. Xin Liu, Weijia Zhang, Min-Ling Zhang |
| 2025 | HAR-former: Hybrid Transformer with an Adaptive Time-Frequency Representation Matrix for Long-Term Series Forecasting. Kenghao Zheng, Zi Long, Shuxin Wang |
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| 2025 | Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks. Felix Jimenez, Matthias Katzfuss |
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| 2025 | Weighted Sum of Gaussian Process Latent Variable Models. James Odgers, Ruby Sedgwick, Chrysoula Kappatou, Ruth Misener, Sarah Filippi |
| 2025 | What Ails Generative Structure-based Drug Design: Expressivity is Too Little or Too Much? Rafal Karczewski, Samuel Kaski, Markus Heinonen, Vikas K. Garg |
| 2025 | What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization. Yufeng Zhang, Fengzhuo Zhang, Zhuoran Yang, Zhaoran Wang |
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| 2025 | Your copula is a classifier in disguise: classification-based copula density estimation. David Huk, Mark Steel, Ritabrata Dutta |
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