Poster "bayesian neural networks" Papers
16 papers found
Conference
Bayesian Treatment of the Spectrum of the Empirical Kernel in (Sub)Linear-Width Neural Networks
Ouns El Harzli, Bernardo Grau
ICLR 2025
Bridging the Gap between Variational Inference and Stochastic Gradient MCMC in Function Space
Mengjing Wu, Junyu Xuan, Jie Lu
ICLR 2025
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification
Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar et al.
ICLR 2025arXiv:2405.15047
5
citations
Deep Kernel Posterior Learning under Infinite Variance Prior Weights
Jorge Loría, Anindya Bhadra
ICLR 2025arXiv:2410.01284
Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks
Emanuel Sommer, Jakob Robnik, Giorgi Nozadze et al.
ICLR 2025arXiv:2502.06335
5
citations
Variational Bayesian Pseudo-Coreset
Hyungi Lee, Seungyoo Lee, Juho Lee
ICLR 2025arXiv:2502.21143
VIKING: Deep variational inference with stochastic projections
Samuel Matthiesen, Hrittik Roy, Nicholas Krämer et al.
NEURIPS 2025arXiv:2510.23684
When narrower is better: the narrow width limit of Bayesian parallel branching neural networks
Zechen Zhang, Haim Sompolinsky
ICLR 2025arXiv:2407.18807
1
citations
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta et al.
ICML 2024arXiv:2402.05015
44
citations
Bayesian Evidential Deep Learning for Online Action Detection
Hongji Guo, Hanjing Wang, Qiang Ji
ECCV 2024
3
citations
Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?
Emanuel Sommer, Lisa Wimmer, Theodore Papamarkou et al.
ICML 2024arXiv:2402.01484
Improving Neural Additive Models with Bayesian Principles
Kouroche Bouchiat, Alexander Immer, Hugo Yèche et al.
ICML 2024arXiv:2305.16905
13
citations
Learning to Explore for Stochastic Gradient MCMC
SeungHyun Kim, Seohyeon Jung, SeongHyeon Kim et al.
ICML 2024arXiv:2408.09140
1
citations
Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models
Gianni Franchi, Olivier Laurent, Maxence Leguéry et al.
CVPR 2024arXiv:2312.15297
16
citations
Partially Stochastic Infinitely Deep Bayesian Neural Networks
Sergio Calvo Ordoñez, Matthieu Meunier, Francesco Piatti et al.
ICML 2024
Reparameterized Importance Sampling for Robust Variational Bayesian Neural Networks
Yunfei Long, Zilin Tian, Liguo Zhang et al.
ICML 2024