Foundation Posteriors for Approximate Probabilistic Inference

19 May 2022

Papers citing "Foundation Posteriors for Approximate Probabilistic Inference"

40 / 40 papers shown

Title
Bernstein Flows for Flexible Posteriors in Variational Bayes Oliver Durr Stephan Hörling Daniel Dold Ivonne Kovylov Beate Sick BDL 68 4 0 11 Feb 2022
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language Alexei Baevski Wei-Ning Hsu Qiantong Xu Arun Babu Jiatao Gu Michael Auli SSL VLM ViT 89 854 0 07 Feb 2022
Modeling Item Response Theory with Stochastic Variational Inference Mike Wu R. Davis B. Domingue Chris Piech Noah D. Goodman CML 39 5 0 26 Aug 2021
Pathfinder: Parallel quasi-Newton variational inference Lu Zhang Bob Carpenter A. Gelman Aki Vehtari 70 40 0 09 Aug 2021
Meta-Learning an Inference Algorithm for Probabilistic Programs Gwonsoo Che Hongseok Yang TPM 28 1 0 01 Mar 2021
Learning Transferable Visual Models From Natural Language Supervision Alec Radford Jong Wook Kim Chris Hallacy Aditya A. Ramesh Gabriel Goh ... Amanda Askell Pamela Mishkin Jack Clark Gretchen Krueger Ilya Sutskever CLIP VLM 828 29,341 0 26 Feb 2021
Transformer Interpretability Beyond Attention Visualization Hila Chefer Shir Gur Lior Wolf 128 664 0 17 Dec 2020
Meta-Learning with Shared Amortized Variational Inference E. Iakovleva Jakob Verbeek Alahari Karteek OOD FedML BDL 42 22 0 27 Aug 2020
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors Yuling Yao Aki Vehtari Andrew Gelman 56 62 0 22 Jun 2020
wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations Alexei Baevski Henry Zhou Abdel-rahman Mohamed Michael Auli SSL 250 5,774 0 20 Jun 2020
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 708 41,894 0 28 May 2020
Quantifying Attention Flow in Transformers Samira Abnar Willem H. Zuidema 134 794 0 02 May 2020
CodeBERT: A Pre-Trained Model for Programming and Natural Languages Zhangyin Feng Daya Guo Duyu Tang Nan Duan Xiaocheng Feng ... Linjun Shou Bing Qin Ting Liu Daxin Jiang Ming Zhou 151 2,613 0 19 Feb 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 341 18,721 0 13 Feb 2020
Variational Item Response Theory: Fast, Accurate, and Expressive Mike Wu R. Davis B. Domingue Chris Piech Noah D. Goodman OffRL 77 55 0 01 Feb 2020
RoBERTa: A Robustly Optimized BERT Pretraining Approach Yinhan Liu Myle Ott Naman Goyal Jingfei Du Mandar Joshi Danqi Chen Omer Levy M. Lewis Luke Zettlemoyer Veselin Stoyanov AIMat 543 24,422 0 26 Jul 2019
Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned Elena Voita David Talbot F. Moiseev Rico Sennrich Ivan Titov 106 1,138 0 23 May 2019
wav2vec: Unsupervised Pre-training for Speech Recognition Steffen Schneider Alexei Baevski R. Collobert Michael Auli SSL 68 418 0 11 Apr 2019
Meta-Amortized Variational Inference and Learning Mike Wu Kristy Choi Noah D. Goodman Stefano Ermon OOD VLM BDL DRL 75 35 0 05 Feb 2019
Pyro: Deep Universal Probabilistic Programming Eli Bingham Jonathan P. Chen M. Jankowiak F. Obermeyer Neeraj Pradhan Theofanis Karaletsos Rohit Singh Paul A. Szerlip Paul Horsfall Noah D. Goodman BDL GP 153 1,053 0 18 Oct 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.7K 94,729 0 11 Oct 2018
An Introduction to Probabilistic Programming Jan-Willem van de Meent Brooks Paige Hongseok Yang Frank Wood GP 68 198 0 27 Sep 2018
Meta-Learning Probabilistic Inference For Prediction Jonathan Gordon J. Bronskill Matthias Bauer Sebastian Nowozin Richard Turner BDL 110 264 0 24 May 2018
Multimodal Generative Models for Scalable Weakly-Supervised Learning Mike Wu Noah D. Goodman DRL 70 380 0 14 Feb 2018
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 658 131,414 0 12 Jun 2017
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models George Tucker A. Mnih Chris J. Maddison John Lawson Jascha Narain Sohl-Dickstein BDL 209 282 0 21 Mar 2017
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables Chris J. Maddison A. Mnih Yee Whye Teh BDL 173 2,529 0 02 Nov 2016
Inference Compilation and Universal Probabilistic Programming T. Le A. G. Baydin Frank Wood UQCV 185 143 0 31 Oct 2016
Edward: A library for probabilistic modeling, inference, and criticism Dustin Tran A. Kucukelbir Adji Bousso Dieng Maja R. Rudolph Dawen Liang David M. Blei 50 301 0 31 Oct 2016
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers Alexander Binder G. Montavon Sebastian Lapuschkin K. Müller Wojciech Samek FAtt 72 461 0 04 Apr 2016
Automatic Differentiation Variational Inference A. Kucukelbir Dustin Tran Rajesh Ranganath Andrew Gelman David M. Blei 104 717 0 02 Mar 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 254 4,787 0 04 Jan 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.1K 193,814 0 10 Dec 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.7K 150,006 0 22 Dec 2014
Generalized Product of Experts for Automatic and Principled Fusion of Gaussian Process Predictions Yanshuai Cao David J. Fleet 41 186 0 28 Oct 2014
Venture: a higher-order probabilistic programming platform with programmable inference Vikash K. Mansinghka Daniel Selsam Yura N. Perov 61 255 0 01 Apr 2014
Neural Variational Inference and Learning in Belief Networks A. Mnih Karol Gregor BDL 169 729 0 31 Jan 2014
Black Box Variational Inference Rajesh Ranganath S. Gerrish David M. Blei DRL BDL 129 1,166 0 31 Dec 2013
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 250 2,621 0 29 Jun 2012
Church: a language for generative models Noah D. Goodman Vikash K. Mansinghka Daniel M. Roy Keith Bonawitz J. Tenenbaum 100 817 0 13 Jun 2012