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3Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries
Y. Zhang, R. Xiong, H. He, and M. Pecht. IEEE Transactions on Vehicular Technology, 67 (7): 5695-5705 (July 2018)
3 years ago by @adulny
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3Deep Sets
M. Zaheer, S. Kottur, S. Ravanbakhsh, B. Poczos, R. Salakhutdinov, and A. Smola. (2017)cite arxiv:1703.06114Comment: NIPS 2017.
a year ago by @adulny
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2Robust discovery of partial differential equations in complex situations
H. Xu, and D. Zhang. Phys. Rev. Res., 3 (3): 033270 (September 2021)
a year ago by @adulny
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2Discovery of Partial Differential Equations from Highly Noisy and Sparse Data with Physics-Informed Information Criterion
H. Xu, J. Zeng, and D. Zhang. Research, (2023)
a year ago by @adulny
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1Deep Kernel Learning
A. Wilson, Z. Hu, R. Salakhutdinov, and E. Xing. (2015)cite arxiv:1511.02222Comment: 19 pages, 6 figures.
3 years ago by @adulny
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3Symbolic Brittleness in Sequence Models: On Systematic Generalization in Symbolic Mathematics
S. Welleck, P. West, J. Cao, and Y. Choi. Proceedings of the AAAI Conference on Artificial Intelligence, 36 (8): 8629-8637 (June 2022)
a year ago by @adulny
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4Learning Mathematical Relations Using Deep Tree Models
S. Wankerl, A. Dulny, G. Götz, and A. Hotho. 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), page 1681-1687. (December 2021)
2 years ago by @adulny
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2Learning values across many orders of magnitude.
H. van Hasselt, A. Guez, M. Hessel, V. Mnih, and D. Silver. NIPS, page 4287-4295. (2016)
2 years ago by @adulny
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4SymbolicGPT: A Generative Transformer Model for Symbolic Regression
M. Valipour, B. You, M. Panju, and A. Ghodsi. (2021)cite arxiv:2106.14131Comment: 11 pages, 4 figures.
a year ago by @adulny
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4Implicit Neural Representations with Periodic Activation Functions
V. Sitzmann, J. Martel, A. Bergman, D. Lindell, and G. Wetzstein. (2020)cite arxiv:2006.09661Comment: Project website: https://vsitzmann.github.io/siren/ Project video: https://youtu.be/Q2fLWGBeaiI.
a year ago by @adulny
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1Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud
W. Shi, Ragunathan, and Rajkumar. (2020)cite arxiv:2003.01251.
2 years ago by @adulny
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7Learning to Simulate Complex Physics with Graph Networks
A. Sanchez-Gonzalez, J. Godwin, T. Pfaff, R. Ying, J. Leskovec, and P. Battaglia. (2020)cite arxiv:2002.09405Comment: Accepted at ICML 2020.
3 years ago by @adulny
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2Latent ODEs for Irregularly-Sampled Time Series
Y. Rubanova, R. Chen, and D. Duvenaud. (2019)cite arxiv:1907.03907.
4 years ago by @adulny
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4Variational Inference with Normalizing Flows
D. Rezende, and S. Mohamed. (2015)cite arxiv:1505.05770Comment: Proceedings of the 32nd International Conference on Machine Learning.
3 years ago by @adulny
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2Universal Physics-Informed Neural Networks: Symbolic Differential Operator Discovery with Sparse Data
L. Podina, B. Eastman, and M. Kohandel. Proceedings of the 40th International Conference on Machine Learning, volume 202 of Proceedings of Machine Learning Research, page 27948--27956. PMLR, (23--29 Jul 2023)
10 months ago by @adulny
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3Learning Mesh-Based Simulation with Graph Networks
T. Pfaff, M. Fortunato, A. Sanchez-Gonzalez, and P. Battaglia. (2020)cite arxiv:2010.03409.
3 years ago by @adulny
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1Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients
B. Petersen, M. Larma, T. Mundhenk, C. Santiago, S. Kim, and J. Kim. International Conference on Learning Representations, (2021)
a year ago by @adulny
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2Active Tuning
S. Otte, M. Karlbauer, and M. Butz. (2020)cite arxiv:2010.03958.
4 years ago by @adulny
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3When are Neural ODE Solutions Proper ODEs?
K. Ott, P. Katiyar, P. Hennig, and M. Tiemann. (2020)cite arxiv:2007.15386.
3 years ago by @adulny
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1Generalizing semi-supervised generative adversarial networks to regression using feature contrasting
G. Olmschenk, Z. Zhu, and H. Tang. (2018)cite arxiv:1811.11269.
4 years ago by @adulny
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3Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries

3Deep Sets

2Robust discovery of partial differential equations in complex situations

2Discovery of Partial Differential Equations from Highly Noisy and Sparse Data with Physics-Informed Information Criterion

1Deep Kernel Learning

3Symbolic Brittleness in Sequence Models: On Systematic Generalization in Symbolic Mathematics

4Learning Mathematical Relations Using Deep Tree Models

2Learning values across many orders of magnitude.

4SymbolicGPT: A Generative Transformer Model for Symbolic Regression

4Implicit Neural Representations with Periodic Activation Functions

1Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud

7Learning to Simulate Complex Physics with Graph Networks

2Latent ODEs for Irregularly-Sampled Time Series

4Variational Inference with Normalizing Flows

2Universal Physics-Informed Neural Networks: Symbolic Differential Operator Discovery with Sparse Data

3Learning Mesh-Based Simulation with Graph Networks

1Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients

2Active Tuning

3When are Neural ODE Solutions Proper ODEs?

1Generalizing semi-supervised generative adversarial networks to regression using feature contrasting

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