Bayesian Deep Learning

BDL

Bayesian Deep Learning is a field that combines Bayesian probability theory with deep learning. It aims to provide a principled way of quantifying uncertainty in neural network predictions.

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AnySleep: a channel-agnostic deep learning system for high-resolution sleep staging in multi-center cohorts Niklas Grieger Jannik Raskob Siamak Mehrkanoon Stephan Bialonski BDL 8 0 0 16 Dec 2025
FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting Xingjian Wu Hanyin Cheng Xiangfei Qiu Zhengyu Li Jilin Hu Chenjuan Guo Bin Yang AI4TS BDL AI4CE 4 0 0 16 Dec 2025
Bridging Artificial Intelligence and Data Assimilation: The Data-driven Ensemble Forecasting System ClimaX-LETKF Akira Takeshima Kenta Shiraishi Atsushi Okazaki Tadashi Tsuyuki Shunji Kotsuki BDL AI4Cl 60 0 0 16 Dec 2025
A variational Bayes latent class approach for EHR-based patient phenotyping in R Brian Buckley Adrian O'Hagan Marie Galligan BDL 0 0 0 16 Dec 2025
From Overfitting to Reliability: Introducing the Hierarchical Approximate Bayesian Neural Network Hayk Amirkhanian Marco F. Huber UQCV BDL 20 0 0 15 Dec 2025
An Open and Reproducible Deep Research Agent for Long-Form Question Answering Ikuya Yamada Wataru Ikeda Ko Yoshida Mengyu Ye Hinata Sugimoto Masatoshi Suzuki Hisanori Ozaki Jun Suzuki LLMAG BDL LRM 12 0 0 15 Dec 2025
Efficient Adaptive Rejection Sampling for Accelerating Speculative Decoding in Large Language Models Chendong Sun mingmin Chen Lei Xu BDL 142 0 0 15 Dec 2025
PAC-Bayes Bounds for Multivariate Linear Regression and Linear Autoencoders Ruixin Guo Ruoming Jin Xinyu Li Yang Zhou BDL 23 0 0 15 Dec 2025
Transport Reversible Jump Markov Chain Monte Carlo with proposals generated by Variational Inference with Normalizing Flows Pingping Yin Xiyun Jiao BDL 4 0 0 14 Dec 2025
Complexity of Markov Chain Monte Carlo for Generalized Linear Models Martin Chak Giacomo Zanella BDL 4 0 0 14 Dec 2025
High-Dimensional Surrogate Modeling for Closed-Loop Learning of Neural-Network-Parameterized Model Predictive Control Sebastian Hirt Valentinus Suwanto Hendrik Alsmeier Maik Pfefferkorn Rolf Findeisen BDL 104 0 0 12 Dec 2025
Latent Chain-of-Thought World Modeling for End-to-End Driving Shuhan Tan Kashyap Chitta Yuxiao Chen Ran Tian Yurong You ... Wenjie Luo Yulong Cao Philipp Krahenbuhl Marco Pavone Boris Ivanovic BDL LRM 152 0 0 11 Dec 2025
Latent-Autoregressive GP-VAE Language Model Yves Ruffenach BDL 56 0 0 10 Dec 2025
QuanvNeXt: An end-to-end quanvolutional neural network for EEG-based detection of major depressive disorder Nabil Anan Orka Ehtashamul Haque Maftahul Jannat Md Abdul Awal Mohammad Ali Moni BDL 60 0 0 10 Dec 2025
Deep Kernel Aalen-Johansen Estimator: An Interpretable and Flexible Neural Net Framework for Competing Risks Xiaobin Shen George H. Chen BDL 20 0 0 08 Dec 2025
Hierarchical Deep Learning for Diatom Image Classification: A Multi-Level Taxonomic Approach Yueying Ke BDL 92 0 0 07 Dec 2025
TopiCLEAR: Topic extraction by CLustering Embeddings with Adaptive dimensional Reduction Aoi Fujita Taichi Yamamoto Yuri Nakayama Ryota Kobayashi BDL 20 0 0 07 Dec 2025
Vector Quantization using Gaussian Variational Autoencoder Tongda Xu Wendi Zheng Jiajun He Jose Miguel Hernandez-Lobato Yan Wang Ya-Qin Zhang Jie Tang DRL BDL MQ 173 0 0 07 Dec 2025
Interpretable Neural Approximation of Stochastic Reaction Dynamics with Guaranteed Reliability Quentin Badolle Arthur Theuer Zhou Fang Ankit Gupta Mustafa Khammash BDL 100 0 0 06 Dec 2025
Exoplanet formation inference using conditional invertible neural networks Remo Burn Victor F. Ksoll Hubert Klahr Thomas Henning 3DPC BDL 76 0 0 05 Dec 2025
Uncertainty Quantification for Scientific Machine Learning using Sparse Variational Gaussian Process Kolmogorov-Arnold Networks (SVGP KAN) Y. Sungtaek Ju BDL 40 0 0 04 Dec 2025
Learning Causality for Longitudinal Data Mouad EL Bouchattaoui CML BDL 173 0 0 04 Dec 2025
On the Limits of Test-Time Compute: Sequential Reward Filtering for Better Inference Yue Yu Qiwei Di Quanquan Gu Dongruo Zhou BDL 97 0 0 04 Dec 2025
Amortized Causal Discovery with Prior-Fitted Networks Mateusz Sypniewski Mateusz Olko Mateusz Gajewski Piotr Miłoś CML BDL 4 0 0 03 Dec 2025
Bayes-DIC Net: Estimating Digital Image Correlation Uncertainty with Bayesian Neural Networks Biao Chen Zhenhua Lei Yahui Zhang Tongzhi Niu DiffM BDL 100 0 0 03 Dec 2025
Walking on the Fiber: A Simple Geometric Approximation for Bayesian Neural Networks Alfredo Reichlin Miguel Vasco Danica Kragic BDL UQCV 112 0 0 01 Dec 2025
Uncertainty Reasoning with Photonic Bayesian Machines F. Brückerhoff-Plückelmann H. Borras S. U. Hulyal L. Meyer X. Ji ... L. McRae P. Schmidt T. J. Kippenberg H. Fröning W. Pernice BDL 31 0 0 01 Dec 2025
A Self-explainable Model of Long Time Series by Extracting Informative Structured Causal Patterns Ziqian Wang Yuxiao Cheng Jinli Suo AI4TS CML BDL 60 0 0 01 Dec 2025
SVRG and Beyond via Posterior Correction Nico Daheim Thomas Möllenhoff Ming Liang Ang Mohammad Emtiyaz Khan BDL 44 0 0 01 Dec 2025
Uncertainty Quantification for Deep Regression using Contextualised Normalizing Flows Adriel Sosa Marco John Daniel Kirwan Alexia Toumpa Simos Gerasimou UQCV BDL 160 0 0 30 Nov 2025
Markovian Scale Prediction: A New Era of Visual Autoregressive Generation Yu Zhang Jingyi Liu Yiwei Shi Qi Zhang Duoqian Miao Changwei Wang Longbing Cao BDL OffRL 91 0 0 28 Nov 2025
Accelerated Execution of Bayesian Neural Networks using a Single Probabilistic Forward Pass and Code Generation Bernhard Klein Falk Selker Hendrik Borras Sophie Steger Franz Pernkopf Holger Fröning UQCV BDL 72 0 0 28 Nov 2025
Early Risk Prediction with Temporally and Contextually Grounded Clinical Language Processing Rochana Chaturvedi Yue Zhou Andrew Boyd Brian T. Layden Mudassir Rashid Lu Cheng Ali Cinar Barbara Di Eugenio BDL 155 0 0 27 Nov 2025
Variational bagging: a robust approach for Bayesian uncertainty quantification Shitao Fan Ilsang Ohn David B. Dunson Lizhen Lin BDL UQCV 281 0 0 25 Nov 2025
Deep Gaussian Process Proximal Policy Optimization Matthijs van der Lende Juan Cardenas-Cartagena GP BDL UQCV 193 0 0 22 Nov 2025
The Finer the Better: Towards Granular-aware Open-set Domain Generalization Yunyun Wang Zheng Duan Xinyue Liao Ke-Jia Chen Songcan Chen BDL VLM 140 0 0 21 Nov 2025
Characterizing Continuous and Discrete Hybrid Latent Spaces for Structural Connectomes Gaurav Rudravaram Lianrui Zuo Adam M. Saunders Michael E. Kim Praitayini Kanakaraj ... Lori L. Beason Held Derek Archer Timothy J. Hohman Daniel C. Moyer Bennett A. Landman BDL 136 0 0 20 Nov 2025
BaGGLS: A Bayesian Shrinkage Framework for Interpretable Modeling of Interactions in High-Dimensional Biological Data Marta S. Lemanczyk Lucas Kock Johanna Schlimme Nadja Klein Bernhard Y. Renard BDL 195 0 0 19 Nov 2025
DeepBlip: Estimating Conditional Average Treatment Effects Over Time Haorui Ma Dennis Frauen Stefan Feuerriegel BDL 155 0 0 18 Nov 2025
Notes on Kernel Methods in Machine Learning Diego Armando Pérez-Rosero Danna Valentina Salazar-Dubois Juan Camilo Lugo-Rojas Andrés Marino Álvarez-Meza Germán Castellanos-Dominguez BDL VLM 128 0 0 18 Nov 2025
Bridging the Gap Between Bayesian Deep Learning and Ensemble Weather Forecasts Xinlei Xiong Wenbo Hu Shuxun Zhou Kaifeng Bi Lingxi Xie Ying Liu Richang Hong Q. Tian BDL UQCV AI4CE 156 0 0 18 Nov 2025
Counterfactual Explainable AI (XAI) Method for Deep Learning-Based Multivariate Time Series Classification Alan G. Paredes Cetina Kaouther Benguessoum Raoni Lourenço Sylvain Kubler AI4TS BDL CML 384 0 0 17 Nov 2025
BlinDNO: A Distributional Neural Operator for Dynamical System Reconstruction from Time-Label-Free data Zhijun Zeng Junqing Chen Zuoqiang Shi BDL 98 0 0 15 Nov 2025
Cacheback: Speculative Decoding With Nothing But Cache Zhiyao Ma In Gim Lin Zhong BDL 138 0 0 15 Nov 2025
StochEP: Stochastic Equilibrium Propagation for Spiking Convergent Recurrent Neural Networks Jiaqi Lin Yi Jiang Abhronil Sengupta BDL 108 0 0 14 Nov 2025
Inferring response times of perceptual decisions with Poisson variational autoencoders Hayden R. Johnson Anastasia N. Krouglova Hadi Vafaii Jacob L. Yates P. J. Gonçalves DRL BDL 328 0 0 14 Nov 2025
Pretrained Joint Predictions for Scalable Batch Bayesian Optimization of Molecular Designs Miles Wang-Henderson Ben Kaufman Edward Williams Ryan Pederson Matteo Rossi Owen Howell Carl Underkoffler Narbe Mardirossian John Parkhill BDL 298 0 0 13 Nov 2025
Expandable and Differentiable Dual Memories with Orthogonal Regularization for Exemplar-free Continual Learning Hyung-Jun Moon Sung-Bae Cho CLL BDL VLM 178 0 0 13 Nov 2025
Strategic Opponent Modeling with Graph Neural Networks, Deep Reinforcement Learning and Probabilistic Topic Modeling Georgios Chalkiadakis Charilaos Akasiadis Gerasimos Koresis Stergios Plataniots Leonidas Bakopoulos BDL AAML 445 0 0 13 Nov 2025
Multiple Treatments Causal Effects Estimation with Task Embeddings and Balanced Representation Learning Yuki Murakami Takumi Hattori Kohsuke Kubota CML BDL 100 0 0 12 Nov 2025

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