Deshwal, Aryan

20 publications

AAAI 2025 Adaptive Experimental Design to Accelerate Scientific Discovery and Engineering Design Aryan Deshwal

NeurIPS 2025 BO4Mob: Bayesian Optimization Benchmarks for High-Dimensional Urban Mobility Problem Seunghee Ryu, Donghoon Kwon, Seongjin Choi, Aryan Deshwal, Seungmo Kang, Carolina Osorio

AAAI 2025 Constraint-Adaptive Policy Switching for Offline Safe Reinforcement Learning Yassine Chemingui, Aryan Deshwal, Honghao Wei, Alan Fern, Jana Doppa

NeurIPS 2025 Online Optimization for Offline Safe Reinforcement Learning Yassine Chemingui, Aryan Deshwal, Alan Fern, Thanh Nguyen-Tang, Jana Doppa

ICML 2024 Learning Surrogates for Offline Black-Box Optimization via Gradient Matching Minh Hoang, Azza Fadhel, Aryan Deshwal, Jana Doppa, Trong Nghia Hoang

AAAI 2024 Offline Model-Based Optimization via Policy-Guided Gradient Search Yassine Chemingui, Aryan Deshwal, Trong Nghia Hoang, Janardhan Rao Doppa

IJCAI 2024 Streamflow Prediction with Uncertainty Quantification for Water Management: A Constrained Reasoning and Learning Approach Mohammed Amine Gharsallaoui, Bhupinderjeet Singh, Supriya Savalkar, Aryan Deshwal, Ananth Kalyanaraman, Kirti Rajagopalan, Janardhan Rao Doppa

AISTATS 2023 Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-Based Embeddings Aryan Deshwal, Sebastian Ament, Maximilian Balandat, Eytan Bakshy, Janardhan Rao Doppa, David Eriksson

NeurIPS 2023 GAUCHE: A Library for Gaussian Processes in Chemistry Ryan-Rhys Griffiths, Leo Klarner, Henry Moss, Aditya Ravuri, Sang Truong, Yuanqi Du, Samuel Stanton, Gary Tom, Bojana Rankovic, Arian Jamasb, Aryan Deshwal, Julius Schwartz, Austin Tripp, Gregory Kell, Simon Frieder, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Johannes Peter Dürholt, Saudamini Chaurasia, Ji Won Park, Felix Strieth-Kalthoff, Alpha Lee, Bingqing Cheng, Alan Aspuru-Guzik, Philippe Schwaller, Jian Tang

AAAI 2022 Bayesian Optimization over Permutation Spaces Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Dae Hyun Kim

ICML 2021 Bayesian Optimization over Hybrid Spaces Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa

NeurIPS 2021 Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces Aryan Deshwal, Jana Doppa

AAAI 2021 Mercer Features for Efficient Combinatorial Bayesian Optimization Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa

JAIR 2021 Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa

AAAI 2020 Multi-Fidelity Multi-Objective Bayesian Optimization: An Output Space Entropy Search Approach Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa

AAAI 2020 Optimizing Discrete Spaces via Expensive Evaluations: A Learning to Search Framework Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Alan Fern

AAAI 2020 Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization Syrine Belakaria, Aryan Deshwal, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa

IJCAI 2019 Learning and Inference for Structured Prediction: A Unifying Perspective Aryan Deshwal, Janardhan Rao Doppa, Dan Roth

NeurIPS 2019 Max-Value Entropy Search for Multi-Objective Bayesian Optimization Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa

IJCAI 2019 Randomized Greedy Search for Structured Prediction: Amortized Inference and Learning Chao Ma, F. A. Rezaur Rahman Chowdhury, Aryan Deshwal, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth