Publications

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Aryan Deshwal, Sait Cakmak, Yuhou Xia, David Eriksson. Sample-Efficient Bayesian Optimization with Transfer Learning for Heterogeneous Search Spaces. AutoML Conference (Workshop Track), 2024.

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Eric S. Chen, Alaleh Ahmadianshalchi, Sonja S. Sparks, Chuchu Chen, Aryan Deshwal, Janardhan Rao Doppa, Kaiyan Qiu. Machine Learning Enabled Design and Optimization for 3D‐Printing of High‐Fidelity Presurgical Organ Models. Advanced Materials Technologies, 2024.

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Minh Hoang, Azza Fadhel, Aryan Deshwal, Jana Doppa, Trong Nghia Hoang. Learning Surrogates for Offline Black-Box Optimization via Gradient Matching. Forty-first International Conference on Machine Learning (ICML), 2024.

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Mohammed Amine Gharsallaoui, Bhupinderjeet Singh, Supriya Savalkar, Aryan Deshwal, Yan Yan, Ananth Kalyanaraman, Kirti Rajagopalan, Janardhan Rao Doppa. Streamflow Prediction with Uncertainty Quantification for Water Management. Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI), 2024.

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Yassine Chemingui, Aryan Deshwal, Nghia Hoang, Janardhan Rao Doppa. Offline Model-based Black-Box Optimization via Policy-guided Gradient Search. Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2024.

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Nickolas Gantzler, Aryan Deshwal, Janardhan Rao Doppa, Cory Simon. Multi-fidelity Bayesian Optimization of Covalent Organic Frameworks for Xenon/Krypton Separations. Digitial Discovery Journal, Royal Society of Chemistry, 2023.

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Ryan-Rhys Griffiths, et al. Gauche - A Library for Gaussian Processes in Chemistry. Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023.

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Aryan Deshwal, Sebastian Ament, Maximilian Balandat, Eytan Bakshy, Janardhan Rao Doppa, David Eriksson. Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings. Twenty-Sixth International Conference on Artificial Intelligence and Statistics (AISTATS), 2023.

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Gaurav Narang, Aryan Deshwal, Raid Ayoub, Michael Kishinevsky, Janardhan Rao Doppa, Partha Pratim Pande. Dynamic Power Management in Large Manycore Systems - A Learning-to-Search Framework. ACM Transactions on Design Automation of Electronic Systems (TODAES), 2023.

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Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Dae Hyun Kim. Bayesian Optimization over Permutation Spaces. Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), 2022.

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Aryan Deshwal, Janardhan Rao Doppa. Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces. Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), 2021.

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Aryan Deshwal, Cory Simon, Janardhan Rao Doppa. Bayesian Optimization of Nanoporous Materials. Molecular Systems Design and Engineering Journal, Royal Society of Chemistry, 2021.

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Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa. Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization. Journal of Artificial Intelligence Research (JAIR), 2021.

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Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa. Bayesian Optimization over Hybrid Spaces. Thirty-eighth International Conference on Machine Learning (ICML), 2021.

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Aryan Deshwal, Syrine Belakaria, Ganapati Bhat, Janardhan Rao Doppa, Partha Pratim Pande. Learning Pareto-Frontier Resource Management Policies for Heterogeneous SoCs - An Information-Theoretic Approach. Proceedings of 58th IEEE/ACM Design Automation Conference (DAC), 2021.

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Biresh Kumar Joardar, Aryan Deshwal, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty. High-Throughput Training of Deep CNNs on ReRAM-based Heterogeneous Architectures via Optimized Normalization Layers. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2021.

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Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa. Mercer Features for Efficient Combinatorial Bayesian Optimization. Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021.

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Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa. Scalable Combinatorial Bayesian Optimization with Tractable Statistical models. NeurIPS Workshop on Engineering Modeling, Simulation, and Design, 2020.

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Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa. Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints. NeurIPS Workshop on Machine Learning and the Physical Sciences, 2020.

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Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa. Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations. NeurIPS Workshop on Engineering Modeling, Simulation, and Design, 2020.

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Syrine Belakaria, Aryan Deshwal, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa. Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization. AAAI Conference on Artificial Intelligence (AAAI), 2020.

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Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Alan Fern. Optimizing Discrete Spaces via Expensive Evaluations: A Learning to Search Framework. AAAI Conference on Artificial Intelligence (AAAI), 2020.

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Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa. Multi-Fidelity Multi-Objective Bayesian Optimization, An Output Space Entropy Search Approach. AAAI Conference on Artificial Intelligence (AAAI), 2020.

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Zhiyuan Zhou, Syrine Belakaria, Aryan Deshwal, Wookpyo Hong, Janardhan Rao Doppa, Partha Pratim Pande, Deukhyoun Heo. Design of Multi-Output Switched-Capacitor Voltage Regulator via Machine Learning. 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2020.

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Nitthilan Kanappan Jayakodi, Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa. Design and Optimization of Energy-Accuracy Tradeoff Networks for Mobile Platforms via Pretrained Deep Models. ACM Transactions on Embedded Computing Systems (TECS), 2020.

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Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa. Max-value Entropy Search for Multi-Objective Bayesian Optimization. Advances in Neural Information Processing Systems (NeurIPS), 2019.

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Aryan Deshwal, Nitthilan Kanappan Jayakodi, Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande. MOOS: A multi-objective design space exploration and optimization framework for NoC enabled manycore systems. ACM Transactions on Embedded Computing Systems (TECS), 2019.

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Paul Bogdan, Fan Chen, Aryan Deshwal, Janardhan Rao Doppa, Biresh Kumar Joardar, Hai Li, Shahin Nazarian, Linghao Song, Yao Xiao. Taming extreme heterogeneity via machine learning based design of autonomous manycore systems. Proceedings of the International Conference on Hardware/Software Codesign and System Synthesis Companion (CODES/ISSS), 2019.

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Chao Ma, FA Rezaur Rahman Chowdhury, Aryan Deshwal, Md Rakibul Islam, Janardhan Rao Doppa, Dan Roth. Randomized greedy search for structured prediction: amortized inference and learning. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2019.

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Aryan Deshwal, Janardhan Rao Doppa, Dan Roth. Learning and inference for structured prediction: a unifying perspective. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2019.

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