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Calvin Tsay
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2020 – today
- 2024
- [j10]Radu Burtea, Calvin Tsay
:
Constrained continuous-action reinforcement learning for supply chain inventory management. Comput. Chem. Eng. 181: 108518 (2024) - [j9]Tom McDonald, Calvin Tsay
Mixed-integer optimisation of graph neural networks for computer-aided molecular design. Comput. Chem. Eng. 185: 108660 (2024) - [i25]Joel A. Paulson, Calvin Tsay:
Bayesian optimization as a flexible and efficient design framework for sustainable process systems. CoRR abs/2401.16373 (2024) - [i24]Jose Pablo Folch, Calvin Tsay, Robert M. Lee, Behrang Shafei, Weronika Ormaniec, Andreas Krause, Mark van der Wilk, Ruth Misener, Mojmír Mutný:
Transition Constrained Bayesian Optimization via Markov Decision Processes. CoRR abs/2402.08406 (2024) - [i23]Jixiang Qing, Becky D. Langdon, Robert M. Lee, Behrang Shafei, Mark van der Wilk, Calvin Tsay, Ruth Misener:
System-Aware Neural ODE Processes for Few-Shot Bayesian Optimization. CoRR abs/2406.02352 (2024) - [i22]Philip Sosnin, Mark Niklas Müller, Maximilian Baader, Calvin Tsay, Matthew Wicker:
Certified Robustness to Data Poisoning in Gradient-Based Training. CoRR abs/2406.05670 (2024) - [i21]Matthew Wicker, Philip Sosnin, Adrianna Janik, Mark N. Müller, Adrian Weller, Calvin Tsay:
Certificates of Differential Privacy and Unlearning for Gradient-Based Training. CoRR abs/2406.13433 (2024) - [i20]Maximilian Bloor, Akhil Ahmed, Niki Kotecha, Mehmet Mercangöz, Calvin Tsay, Ehecatl Antonio del Rio-Chanona:
Control-Informed Reinforcement Learning for Chemical Processes. CoRR abs/2408.13566 (2024) - [i19]Yilin Xie, Shiqiang Zhang, Joel A. Paulson, Calvin Tsay:
Global Optimization of Gaussian Process Acquisition Functions Using a Piecewise-Linear Kernel Approximation. CoRR abs/2410.16893 (2024) - [i18]Maximilian Bloor, José Torraca, Ilya Orson Sandoval, Akhil Ahmed, Martha White, Mehmet Mercangöz, Calvin Tsay, Ehecatl Antonio del Rio-Chanona, Max Mowbray:
PC-Gym: Benchmark Environments For Process Control Problems. CoRR abs/2410.22093 (2024) - [i17]Mujin Cheon, Jay H. Lee, Dong-Yeun Koh, Calvin Tsay:
EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization. CoRR abs/2411.00171 (2024) - 2023
- [j8]Jose Pablo Folch
Combining multi-fidelity modelling and asynchronous batch Bayesian Optimization. Comput. Chem. Eng. 172: 108194 (2023) - [c7]Shudian Zhao
Model-Based Feature Selection for Neural Networks: A Mixed-Integer Programming Approach. LION 2023: 223-238 - [c6]Shiqiang Zhang, Juan S. Campos, Christian Feldmann, David Walz, Frederik Sandfort, Miriam Mathea, Calvin Tsay, Ruth Misener:
Optimizing over trained GNNs via symmetry breaking. NeurIPS 2023 - [i16]Jaime Sabal Bermúdez, Antonio del Rio-Chanona, Calvin Tsay:
Distributional constrained reinforcement learning for supply chain optimization. CoRR abs/2302.01727 (2023) - [i15]Shudian Zhao, Calvin Tsay, Jan Kronqvist:
Model-based feature selection for neural networks: A mixed-integer programming approach. CoRR abs/2302.10344 (2023) - [i14]Joey Huchette, Gonzalo Muñoz, Thiago Serra, Calvin Tsay:
When Deep Learning Meets Polyhedral Theory: A Survey. CoRR abs/2305.00241 (2023) - [i13]Jose Pablo Folch, James Odgers, Shiqiang Zhang, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener:
Practical Path-based Bayesian Optimization. CoRR abs/2312.00622 (2023) - [i12]Tom McDonald, Calvin Tsay, Artur M. Schweidtmann, Neil Yorke-Smith:
Mixed-Integer Optimisation of Graph Neural Networks for Computer-Aided Molecular Design. CoRR abs/2312.01228 (2023) - 2022
- [j7]Francesco Ceccon, Jordan Jalving, Joshua Haddad, Alexander Thebelt, Calvin Tsay, Carl D. Laird, Ruth Misener:
OMLT: Optimization & Machine Learning Toolkit. J. Mach. Learn. Res. 23: 349:1-349:8 (2022) - [c5]Jose Pablo Folch, Shiqiang Zhang, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener:
SnAKe: Bayesian Optimization with Pathwise Exploration. NeurIPS 2022 - [c4]Alexander Thebelt, Calvin Tsay, Robert M. Lee, Nathan Sudermann-Merx, David Walz, Behrang Shafei, Ruth Misener:
Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces. NeurIPS 2022 - [i11]Alexander Thebelt, Johannes Wiebe, Jan Kronqvist, Calvin Tsay, Ruth Misener:
Maximizing information from chemical engineering data sets: Applications to machine learning. CoRR abs/2201.10035 (2022) - [i10]Jose Pablo Folch, Shiqiang Zhang, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener:
SnAKe: Bayesian Optimization with Pathwise Exploration. CoRR abs/2202.00060 (2022) - [i9]Francesco Ceccon, Jordan Jalving, Joshua Haddad, Alexander Thebelt, Calvin Tsay, Carl D. Laird, Ruth Misener:
OMLT: Optimization & Machine Learning Toolkit. CoRR abs/2202.02414 (2022) - [i8]Jan Kronqvist, Ruth Misener, Calvin Tsay:
P-split formulations: A class of intermediate formulations between big-M and convex hull for disjunctive constraints. CoRR abs/2202.05198 (2022) - [i7]Alexander Thebelt, Calvin Tsay, Robert M. Lee, Nathan Sudermann-Merx, David Walz, Behrang Shafei, Ruth Misener:
Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces. CoRR abs/2207.00879 (2022) - [i6]Jose Pablo Folch, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener
Combining Multi-Fidelity Modelling and Asynchronous Batch Bayesian Optimization. CoRR abs/2211.06149 (2022) - 2021
- [j6]Calvin Tsay:
Sobolev trained neural network surrogate models for optimization. Comput. Chem. Eng. 153: 107419 (2021) - [c3]Jan Kronqvist
Between Steps: Intermediate Relaxations Between Big-M and Convex Hull Formulations. CPAIOR 2021: 299-314 - [c2]Calvin Tsay, Jan Kronqvist, Alexander Thebelt, Ruth Misener:
Partition-Based Formulations for Mixed-Integer Optimization of Trained ReLU Neural Networks. NeurIPS 2021: 3068-3080 - [i5]Jan Kronqvist, Ruth Misener, Calvin Tsay:
Between steps: Intermediate relaxations between big-M and convex hull formulations. CoRR abs/2101.12708 (2021) - [i4]Calvin Tsay, Jan Kronqvist, Alexander Thebelt, Ruth Misener:
Partition-based formulations for mixed-integer optimization of trained ReLU neural networks. CoRR abs/2102.04373 (2021) - [i3]Alexander Thebelt, Calvin Tsay, Robert M. Lee, Nathan Sudermann-Merx, David Walz, Tom Tranter, Ruth Misener:
Multi-Objective Constrained Optimization for Energy Applications via Tree Ensembles. CoRR abs/2111.03140 (2021) - 2020
- [i2]Calvin Tsay, Yanan Cao, Yajun Wang, Jesus Flores-Cerrillo, Michael Baldea:
Identification and online updating of dynamic models for demand response of an industrial air separation unit. CoRR abs/2009.13999 (2020)
2010 – 2019
- 2019
- [j5]Calvin Tsay, Ankur Kumar, Jesus Flores-Cerrillo, Michael Baldea:
Optimal demand response scheduling of an industrial air separation unit using data-driven dynamic models. Comput. Chem. Eng. 126: 22-34 (2019) - [c1]Calvin Tsay, Zheng Li:
Automating Visual Inspection of Lyophilized Drug Products With Multi-Input Deep Neural Networks. CASE 2019: 1802-1807 - [i1]Calvin Tsay, Michael Baldea:
Learning latent variable dynamic models for integrated production scheduling and control. CoRR abs/1904.04796 (2019) - 2018
- [j4]Calvin Tsay, Richard C. Pattison, Michael R. Piana, Michael Baldea
A survey of optimal process design capabilities and practices in the chemical and petrochemical industries. Comput. Chem. Eng. 112: 180-189 (2018) - [j3]Lisia S. Dias, Richard C. Pattison, Calvin Tsay, Michael Baldea, Marianthi G. Ierapetritou:
A simulation-based optimization framework for integrating scheduling and model predictive control, and its application to air separation units. Comput. Chem. Eng. 113: 139-151 (2018) - 2017
- [j2]Richard C. Pattison, Calvin Tsay, Michael Baldea:
Pseudo-transient models for multiscale, multiresolution simulation and optimization of intensified reaction/separation/recycle processes: Framework and a dimethyl ether production case study. Comput. Chem. Eng. 105: 161-172 (2017) - [j1]Calvin Tsay, Richard C. Pattison, Michael Baldea, Ben G. Weinstein, Steven J. Hodson, Robert D. Johnson:
A superstructure-based design of experiments framework for simultaneous domain-restricted model identification and parameter estimation. Comput. Chem. Eng. 107: 408-426 (2017)
Coauthor Index
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last updated on 2024-12-11 20:46 CET by the dblp team
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