Aryan Deshwal

According to our database, Aryan Deshwal authored at least 29 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Sample-Efficient Bayesian Optimization with Transfer Learning for Heterogeneous Search Spaces.

Aryan Deshwal, Sait Cakmak, Yuhou Xia, David Eriksson

CoRR, 2024

Streamflow Prediction with Uncertainty Quantification for Water Management: A Constrained Reasoning and Learning Approach.

Mohammed Amine Gharsallaoui, Bhupinderjeet Singh, Supriya Savalkar, Aryan Deshwal, Yan Yan, Ananth Kalyanaraman, Kirti Rajagopalan, Janardhan Rao Doppa

CoRR, 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

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Learning Surrogates for Offline Black-Box Optimization via Gradient Matching.

Minh Hoang, Azza Fadhel, Aryan Deshwal, Jana Doppa, Trong Nghia Hoang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Offline Model-Based Optimization via Policy-Guided Gradient Search.

Yassine Chemingui, Aryan Deshwal, Trong Nghia Hoang, Janardhan Rao Doppa

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Dynamic Power Management in Large Manycore Systems: A Learning-to-Search Framework.

Gaurav Narang, Aryan Deshwal, Raid Ayoub, Michael Kishinevsky, Janardhan Rao Doppa, Partha Pratim Pande

ACM Trans. Design Autom. Electr. Syst., September, 2023

GAUCHE: A Library for Gaussian Processes in Chemistry.

Ryan-Rhys Griffiths, Leo Klarner, Henry B. Moss, Aditya Ravuri, Sang Truong, Yuanqi Du, Samuel Stanton, Gary Tom, Bojana Rankovic, Arian Rokkum 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 A. Lee, Bingqing Cheng, Alán Aspuru-Guzik, Philippe Schwaller, Jian Tang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

High-Throughput Training of Deep CNNs on ReRAM-Based Heterogeneous Architectures via Optimized Normalization Layers.

Biresh Kumar Joardar, Aryan Deshwal, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

Bayesian Optimization over Permutation Spaces.

Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Dae Hyun Kim

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization.

Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa

J. Artif. Intell. Res., 2021

Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces.

Aryan Deshwal, Janardhan Rao Doppa

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Bayesian Optimization over Hybrid Spaces.

Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Pareto-Frontier Resource Management Policies for Heterogeneous SoCs: An Information-Theoretic Approach.

Aryan Deshwal, Syrine Belakaria, Ganapati Bhat, Janardhan Rao Doppa, Partha Pratim Pande

Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

Mercer Features for Efficient Combinatorial Bayesian Optimization.

Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Design and Optimization of Energy-Accuracy Tradeoff Networks for Mobile Platforms via Pretrained Deep Models.

Nitthilan Kanappan Jayakodi, Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa

ACM Trans. Embed. Comput. Syst., 2020

Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations.

Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa

CoRR, 2020

Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints.

Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa

CoRR, 2020

Scalable Combinatorial Bayesian Optimization with Tractable Statistical models.

Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa

CoRR, 2020

Uncertainty aware Search Framework for Multi-Objective Bayesian Optimization with Constraints.

Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa

CoRR, 2020

Design of Multi-Output Switched-Capacitor Voltage Regulator via Machine Learning.

Zhiyuan Zhou, Syrine Belakaria, Aryan Deshwal, Wookpyo Hong, Janardhan Rao Doppa, Partha Pratim Pande, Deukhyoun Heo

Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

Optimizing Discrete Spaces via Expensive Evaluations: A Learning to Search Framework.

Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Alan Fern

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization.

Syrine Belakaria, Aryan Deshwal, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Multi-Fidelity Multi-Objective Bayesian Optimization: An Output Space Entropy Search Approach.

Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

MOOS: A Multi-Objective Design Space Exploration and Optimization Framework for NoC Enabled Manycore Systems.

Aryan Deshwal, Nitthilan Kannappan Jayakodi, Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande

ACM Trans. Embed. Comput. Syst., 2019

Max-value Entropy Search for Multi-Objective Bayesian Optimization.

Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning and Inference for Structured Prediction: A Unifying Perspective.

Aryan Deshwal, Janardhan Rao Doppa, Dan Roth

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 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

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Taming extreme heterogeneity via machine learning based design of autonomous manycore systems.

Paul Bogdan, Fan Chen, Aryan Deshwal, Janardhan Rao Doppa, Biresh Kumar Joardar, Hai (Helen) Li, Shahin Nazarian, Linghao Song, Yao Xiao

Proceedings of the International Conference on Hardware/Software Codesign and System Synthesis Companion, 2019