Amortized In-Context Bayesian Posterior Estimation

10 February 2025

Papers citing "Amortized In-Context Bayesian Posterior Estimation"

26 / 26 papers shown

Title
Effortless, Simulation-Efficient Bayesian Inference using Tabular Foundation Models Julius Vetter Manuel Gloeckler Daniel Gedon Jakob H Macke 74 0 0 24 Apr 2025
Compositional Score Modeling for Simulation-based Inference Tomas Geffner George Papamakarios A. Mnih 79 27 0 28 Sep 2022
A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models Oleg Arenz Philipp Dahlinger Zihan Ye Michael Volpp Gerhard Neumann 65 15 0 23 Sep 2022
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes Shivam Garg Dimitris Tsipras Percy Liang Gregory Valiant 95 479 0 01 Aug 2022
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second Noah Hollmann Samuel G. Müller Katharina Eggensperger Frank Hutter 60 283 0 05 Jul 2022
Transformers Can Do Bayesian Inference Samuel G. Müller Noah Hollmann Sebastian Pineda Arango Josif Grabocka Frank Hutter BDL UQCV 62 160 0 20 Dec 2021
Path Integral Sampler: a stochastic control approach for sampling Qinsheng Zhang Yongxin Chen DiffM 63 107 0 30 Nov 2021
Kernel Identification Through Transformers F. Simpson Ian Davies V. Lalchand A. Vullo N. Durrande C. Rasmussen 27 10 0 15 Jun 2021
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 262 6,293 0 26 Nov 2020
Meta-Learning in Neural Networks: A Survey Timothy M. Hospedales Antreas Antoniou P. Micaelli Amos Storkey OOD 294 1,950 0 11 Apr 2020
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 133 1,662 0 05 Dec 2019
The frontier of simulation-based inference Kyle Cranmer Johann Brehmer Gilles Louppe AI4CE 103 834 0 04 Nov 2019
Convolutional Conditional Neural Processes Jonathan Gordon W. Bruinsma Andrew Y. K. Foong James Requeima Yann Dubois Richard Turner BDL 53 164 0 29 Oct 2019
Attentive Neural Processes Hyunjik Kim A. Mnih Jonathan Richard Schwarz M. Garnelo S. M. Ali Eslami Dan Rosenbaum Oriol Vinyals Yee Whye Teh 77 436 0 17 Jan 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 90 1,043 0 18 Oct 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 203 3,110 0 09 Jul 2018
Conditional Neural Processes M. Garnelo Dan Rosenbaum Chris J. Maddison Tiago Ramalho D. Saxton Murray Shanahan Yee Whye Teh Danilo Jimenez Rezende S. M. Ali Eslami UQCV BDL 48 688 0 04 Jul 2018
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes Erin Grant Chelsea Finn Sergey Levine Trevor Darrell Thomas Griffiths BDL 63 505 0 26 Jan 2018
Learning to Compare: Relation Network for Few-Shot Learning Flood Sung Yongxin Yang Li Zhang Tao Xiang Philip Torr Timothy M. Hospedales 199 4,035 0 16 Nov 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 430 129,831 0 12 Jun 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 754 11,793 0 09 Mar 2017
Matching Networks for One Shot Learning Oriol Vinyals Charles Blundell Timothy Lillicrap Koray Kavukcuoglu Daan Wierstra VLM 286 7,286 0 13 Jun 2016
Recognition Networks for Approximate Inference in BN20 Networks Q. Morris BDL 106 27 0 10 Jan 2013
Expectation Propagation for approximate Bayesian inference T. Minka 101 1,906 0 10 Jan 2013
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 191 2,605 0 29 Jun 2012
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo Matthew D. Hoffman Andrew Gelman 131 4,275 0 18 Nov 2011