2024

D Huang, Y Guo, L Acerbi, S kaski. “Amortized Bayesian Experimental Design for Decision-Making”. NeurIPS 2024.
X Zhang, D Huang, S Kaski, J Martinelli. “PABBO: Preferential Amortized Black-Box Optimization”. (openreview).
P Chang*, N Loka*, D Huang*, U Remes, S Kaski, L Acerbi. “Amortized Probabilistic Conditioning for Optimization, Simulation and Inference”. arXiv:2410.15320.
A Bharti, D Huang, S Kaski, F-X Briol. “Cost-aware Simulation-based Inference”. arXiv:2410.07930.

2023

D Huang*, A Bharti*, A Souza, L Acerbi, S Kaski. “Learning Robust Statistics for Simulation-based Inference under Model Misspecification”. NeurIPS 2023. (paper, code, website, poster)
D Huang, M Haussmann, U Remes, ST John, G Clarte, KS Luck, S Kaski, L Acerbi. “Practical Equivariances via Relational Conditional Neural Processes”. NeurIPS 2023. (paper, code, website, poster)
D Huang, L Filstroff, P Mikkola, M Todorovic, S Kaski. “Augmenting Bayesian Optimization with Preference-based Expert Feedback”. ICML Workshop 2023 on The Many Facets of Preference-based Learning. (paper, code)

D Huang. “Bayesian Optimization Augmented with Actively Elicited Expert Knowledge”. Master thesis. (paper)

D Huang, RF Perez. “SSELDnet: A Fully End-to-End Sample-Level Framework for Sound Event Localization and Detection”. DCASE 2021. (paper, code)

R Zheng, Y Zhang, D Huang, Q Chen. “Sequential Convolution and Runge-Kutta Residual Architecture for Image Compressed Sensing”. ECCV 2020. (paper, code)
D Huang. “Multi-Modal Fusion for Fake News Detection”. Bachelor thesis. (code)