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cs.LG2023★ 2 cited
Clarifying Trust of Materials Property Predictions using Neural Networks with Distribution-Specific Uncertainty Quantification
Cameron Gruich, Varun Madhavan, Yixin Wang +1
It is critical that machine learning (ML) model predictions be trustworthy for high-throughput catalyst discovery approaches. Uncertainty quantification (UQ) methods allow estimati…
cs.LG2022★ 77 cited
AI Poincaré 2.0: Machine Learning Conservation Laws from Differential Equations
Ziming Liu, Varun Madhavan, Max Tegmark
We present a machine learning algorithm that discovers conservation laws from differential equations, both numerically (parametrized as neural networks) and symbolically, ensuring…