Nasrulloh Ratu Bagus Satrio Loka — accepted AI-conference papers

2026

Efficient Autoregressive Inference for Transformer Probabilistic Models

Conor Hassan, Nasrulloh Ratu Bagus Satrio Loka, Cen-You Li, Daolang Huang, Paul Edmund Chang, Yang Yang +3

ICLR 2026poster

Transformer-based models for amortized probabilistic inference, such as neural processes, prior-fitted networks, and tabular foundation models, excel at single-pass *marginal* prediction. However, many real-world applications require coherent *joint distributions* that capture dependencies between p…

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2026

PriorGuide: Test-Time Prior Adaptation for Simulation-Based Inference

Yang Yang, Severi Rissanen, Paul Edmund Chang, Nasrulloh Ratu Bagus Satrio Loka, Daolang Huang, Arno Solin +2

ICLR 2026poster

Amortized simulator-based inference offers a powerful framework for tackling Bayesian inference in computational fields such as engineering or neuroscience, increasingly leveraging modern generative methods like diffusion models to map observed data to model parameters or future predictions. These a…

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2025

Amortized Probabilistic Conditioning for Optimization, Simulation and Inference

Paul Edmund Chang, Nasrulloh Ratu Bagus Satrio Loka, Daolang Huang, Ulpu Remes, Samuel Kaski, Luigi Acerbi

AISTATS 2025poster

Amortized meta-learning methods based on pre-training have propelled fields like natural language processing and vision. Transformer-based neural processes and their variants are leading models for probabilistic meta-learning with a tractable objective. Often trained on synthetic data, these models…

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