Natural-Parameter Networks: A Class of Probabilistic Neural Networks

2 November 2016

Papers citing "Natural-Parameter Networks: A Class of Probabilistic Neural Networks"

47 / 47 papers shown

Title
Token-Level Uncertainty Estimation for Large Language Model Reasoning Tunyu Zhang Haizhou Shi Yibin Wang Hengyi Wang Xiaoxiao He ... Ligong Han Kai Xu Huatian Zhang Dimitris N. Metaxas Hao Wang LRM 113 0 0 16 May 2025
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models Yibin Wang Haizhou Shi Ligong Han Dimitris N. Metaxas Hao Wang BDL UQLM 233 13 0 28 Jan 2025
Training-Free Bayesianization for Low-Rank Adapters of Large Language Models Haizhou Shi Yibin Wang Ligong Han Huatian Zhang Hao Wang UQCV 231 2 0 07 Dec 2024
On Calibration of LLM-based Guard Models for Reliable Content Moderation Hongfu Liu Hengguan Huang Hao Wang Xiangming Gu Ye Wang 188 4 0 14 Oct 2024
Variational Language Concepts for Interpreting Foundation Language Models Hengyi Wang Shiwei Tan Zhiqing Hong Desheng Zhang Hao Wang 148 3 0 04 Oct 2024
Probabilistic Conceptual Explainers: Trustworthy Conceptual Explanations for Vision Foundation Models Hengyi Wang Shiwei Tan Hao Wang BDL 126 7 0 18 Jun 2024
Towards Domain Adaptive Neural Contextual Bandits Ziyan Wang Hao Wang Hao Wang 220 0 0 13 Jun 2024
Delving into Differentially Private Transformer Youlong Ding Xueyang Wu Yining Meng Yonggang Luo Hao Wang Weike Pan 130 5 0 28 May 2024
Uncertainty Quantification via Stable Distribution Propagation Felix Petersen Aashwin Mishra Hilde Kuehne Christian Borgelt Oliver Deussen Mikhail Yurochkin UQCV 73 6 0 13 Feb 2024
Bootstrap Your Own Variance Polina Turishcheva Jason Ramapuram Sinead Williamson Dan Busbridge Eeshan Gunesh Dhekane Russ Webb UQCV 64 0 0 06 Dec 2023
Single-shot Bayesian approximation for neural networks K. Brach Beate Sick Oliver Durr BDL UQCV 29 0 0 24 Aug 2023
PreDiff: Precipitation Nowcasting with Latent Diffusion Models Zhihan Gao Xingjian Shi Boran Han Hongya Wang Xiaoyong Jin Danielle C. Maddix Yi Zhu Mu Li Bernie Wang BDL DiffM 99 64 0 19 Jul 2023
Uncertainty Estimation for Molecules: Desiderata and Methods Tom Wollschlager Nicholas Gao Bertrand Charpentier Mohamed Amine Ketata Stephan Günnemann 93 10 0 20 Jun 2023
Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing Ziyan Wang Hao Wang UQCV 82 0 0 11 Jun 2023
Gibbs Sampling the Posterior of Neural Networks Giovanni Piccioli Emanuele Troiani Lenka Zdeborová 99 3 0 05 Jun 2023
DPFormer: Learning Differentially Private Transformer on Long-Tailed Data Youlong Ding Xueyang Wu Hongya Wang Weike Pan 100 1 0 28 May 2023
EdgeTran: Co-designing Transformers for Efficient Inference on Mobile Edge Platforms Shikhar Tuli N. Jha 76 3 0 24 Mar 2023
CODEBench: A Neural Architecture and Hardware Accelerator Co-Design Framework Shikhar Tuli Chia-Hao Li Ritvik Sharma N. Jha 81 15 0 07 Dec 2022
ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference Nikita Durasov Nik Dorndorf Hieu M. Le Pascal Fua UQCV 89 10 0 21 Nov 2022
FlexiBERT: Are Current Transformer Architectures too Homogeneous and Rigid? Shikhar Tuli Bhishma Dedhia Shreshth Tuli N. Jha 94 14 0 23 May 2022
Learning by Erasing: Conditional Entropy based Transferable Out-Of-Distribution Detection Meng Xing Zhiyong Feng Yong Su Changjae Oh OODD 70 4 0 23 Apr 2022
Context Uncertainty in Contextual Bandits with Applications to Recommender Systems Hao Wang Yifei Ma Hao Ding Yuyang Wang 94 6 0 01 Feb 2022
GOSH: Task Scheduling Using Deep Surrogate Models in Fog Computing Environments Shreshth Tuli G. Casale N. Jennings 73 21 0 16 Dec 2021
Deep Probability Estimation Sheng Liu Aakash Kaku Weicheng Zhu M. Leibovich S. Mohan ... Haoxiang Huang L. Zanna N. Razavian Jonathan Niles-Weed C. Fernandez‐Granda UQCV OOD 97 14 0 21 Nov 2021
Propagating State Uncertainty Through Trajectory Forecasting Boris Ivanovic Yifeng Lin Shubham Shrivastava Punarjay Chakravarty Marco Pavone 149 19 0 07 Oct 2021
Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness Namuk Park S. Kim UQCV AAML 93 21 0 26 May 2021
Quantifying Uncertainty in Deep Spatiotemporal Forecasting Dongxian Wu Liyao (Mars) Gao X. Xiong Matteo Chinazzi Alessandro Vespignani Yi-An Ma Rose Yu AI4TS 97 71 0 25 May 2021
Natural Posterior Network: Deep Bayesian Uncertainty for Exponential Family Distributions Bertrand Charpentier Oliver Borchert Daniel Zügner Simon Geisler Stephan Günnemann UQCV BDL 70 17 0 10 May 2021
Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty Boris Ivanovic Kuan-Hui Lee P. Tokmakov Blake Wulfe R. McAllister Adrien Gaidon Marco Pavone 106 35 0 26 Apr 2021
Sampling-free Variational Inference for Neural Networks with Multiplicative Activation Noise Jannik Schmitt Stefan Roth UQCV 55 6 0 15 Mar 2021
TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning Minchao Wu Michael Norrish Christian J. Walder Amir Dezfouli 61 42 0 19 Feb 2021
Continuously Indexed Domain Adaptation Hao Wang Hao He Dina Katabi MedIm 71 118 0 03 Jul 2020
Probabilistic Pixel-Adaptive Refinement Networks Anne S. Wannenwetsch Stefan Roth 58 14 0 31 Mar 2020
Risk-Aware Planning and Assignment for Ground Vehicles using Uncertain Perception from Aerial Vehicles V. Sharma Maymoonah Toubeh Lifeng Zhou Pratap Tokekar 87 20 0 25 Mar 2020
Sampling-Free Learning of Bayesian Quantized Neural Networks Jiahao Su Milan Cvitkovic Furong Huang BDL MQ UQCV 47 7 0 06 Dec 2019
Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate Lu Mi Hao Wang Yonglong Tian Hao He Nir Shavit UQCV 62 32 0 28 Sep 2019
Sampling-free Epistemic Uncertainty Estimation Using Approximated Variance Propagation Janis Postels Francesco Ferroni Huseyin Coskun Nassir Navab Federico Tombari UQCV UD PER BDL 147 140 0 01 Aug 2019
A General Framework for Uncertainty Estimation in Deep Learning Antonio Loquercio Mattia Segu Davide Scaramuzza UQCV BDL OOD 101 293 0 16 Jul 2019
Vector Quantized Bayesian Neural Network Inference for Data Streams Namuk Park Taekyu Lee Songkuk Kim MQ 62 10 0 12 Jul 2019
Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision Fredrik K. Gustafsson Martin Danelljan Thomas B. Schon OOD UQCV BDL 91 302 0 04 Jun 2019
ProbAct: A Probabilistic Activation Function for Deep Neural Networks Kumar Shridhar JoonHo Lee Hideaki Hayashi Purvanshi Mehta Brian Kenji Iwana Seokjun Kang S. Uchida Sheraz Ahmed Andreas Dengel DiffM AAML 52 32 0 26 May 2019
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling Hao Wang Chengzhi Mao Hao He Mingmin Zhao Tommi Jaakkola Dina Katabi BDL 135 22 0 06 Feb 2019
Inhibited Softmax for Uncertainty Estimation in Neural Networks Marcin Mo.zejko Mateusz Susik Rafal Karczewski UQCV 75 29 0 03 Oct 2018
Lightweight Probabilistic Deep Networks Jochen Gast Stefan Roth UQCV OOD BDL 93 183 0 29 May 2018
Sampling-free Uncertainty Estimation in Gated Recurrent Units with Exponential Families Seong Jae Hwang Ronak R. Mehta Hyunwoo J. Kim Vikas Singh BDL UQCV 61 3 0 19 Apr 2018
Towards Bayesian Deep Learning: A Framework and Some Existing Methods Hao Wang Dit-Yan Yeung BDL 74 225 0 24 Aug 2016
A Survey on Bayesian Deep Learning Hao Wang Dit-Yan Yeung BDL 113 49 0 06 Apr 2016