2 citations · 3 across the 7 of their papers we have counts for
8 papers
Mitigating Representation Gaps in Amortized Bayesian Inference with Auxiliary Supervision
Hans Olischläger, Svenja Jedhoff, Šimon Kucharský +3
Casting Bayesian inference as a neural network optimization problem targeting an amortized posterior is attractive, as it extends to otherwise intractable statistical models and of…
BayesFlow 2: Multi-Backend Amortized Bayesian Inference in Python
Lars Kühmichel, Jerry M. Huang, Valentin Pratz +11
Modern Bayesian inference involves a mixture of computational methods for estimating, validating, and drawing conclusions from probabilistic models as part of principled workflows.…
Unsupervised Continual Learning for Amortized Bayesian Inference
Aayush Mishra, Šimon Kucharský, Paul-Christian Bürkner
Amortized Bayesian Inference (ABI) enables efficient posterior estimation using generative neural networks trained on simulated data, but often suffers from performance degradation…
Improving the Accuracy of Amortized Model Comparison with Self-Consistency
Šimon Kucharský, Aayush Mishra, Daniel Habermann +2
Amortized Bayesian inference (ABI) offers fast, scalable approximations to posterior densities by training neural surrogates on data simulated from the statistical model. However,…
Improving the Accuracy of Amortized Model Comparison with Self-Consistency
Šimon Kucharský, Aayush Mishra, Daniel Habermann +2
Amortized Bayesian model comparison (BMC) enables fast probabilistic ranking of models via simulation-based training of neural surrogates. However, the accuracy of neural surrogate…
Robust Amortized Bayesian Inference with Self-Consistency Losses on Unlabeled Data
Aayush Mishra, Daniel Habermann, Marvin Schmitt +2
Amortized Bayesian inference (ABI) with neural networks can solve probabilistic inverse problems orders of magnitude faster than classical methods. However, ABI is not yet sufficie…
Source-Free and Image-Only Unsupervised Domain Adaptation for Category Level Object Pose Estimation
Prakhar Kaushik, Aayush Mishra, Adam Kortylewski +1
We consider the problem of source-free unsupervised category-level pose estimation from only RGB images to a target domain without any access to source domain data or 3D annotation…
Stress Testing Chain-of-Thought Prompting for Large Language Models
Aayush Mishra, Karan Thakkar
This report examines the effectiveness of Chain-of-Thought (CoT) prompting in improving the multi-step reasoning abilities of large language models (LLMs). Inspired by previous stu…