Wide neural networks with bottlenecks are deep Gaussian processes D Agrawal, T Papamarkou, J Hinkle Journal of Machine Learning Research 21 (175), 1-66, 2020 | 31 | 2020 |
The mechanisms of water exchange: the regulatory roles of multiple interactions in social wasps D Agrawal, I Karsai PLoS One 11 (1), e0145560, 2016 | 11 | 2016 |
A Classification of -invariant Shallow Neural Networks D Agrawal, J Ostrowski Advances in Neural Information Processing Systems 35, 13679-13690, 2022 | 7 | 2022 |
Fiber bundles and Parseval frames D Agrawal, J Knisley arXiv preprint arXiv:1512.03989, 2015 | 5 | 2015 |
The complete structure of linear and nonlinear deformations of frames on a Hilbert space D Agrawal East Tennessee State University, 2016 | 4 | 2016 |
Group-equivariant autoencoder for identifying spontaneously broken symmetries D Agrawal, A Del Maestro, S Johnston, J Ostrowski Physical Review E 107 (5), 054104, 2023 | 2 | 2023 |
Nonparametric Bayesian Deep Learning for Scientific Data Analysis D Agrawal | 1 | 2020 |
Computer-aided detection using non-convolutional neural network Gaussian processes D Agrawal, HJ Yoon, G Tourassi, JD Hinkle Medical Imaging 2019: Computer-Aided Diagnosis 10950, 915-923, 2019 | 1 | 2019 |
Can't Remember Details in Long Documents? You Need Some R&R D Agrawal, S Gao, M Gajek arXiv preprint arXiv:2403.05004, 2024 | | 2024 |
Densely Connected G-invariant Deep Neural Networks with Signed Permutation Representations D Agrawal, J Ostrowski Journal of Machine Learning Research 24 (370), 1-40, 2023 | | 2023 |
Deep Ensemble Kernel Learning D Agrawal, JD Hinkle | | 2020 |
CAFCW 104 Deep Kernel Learning for Information Extraction from Cancer Pathology Reports D Agrawal, A Dubey, G Tourassi, J Hinkle | | 2019 |
Deep kernel learning for information extraction from cancer pathology reports D Agrawal, AK Dubey, G Tourassi, J Hinkle | | 2019 |
A Numerical Model for Nonadiabatic Transitions in Molecules D Agrawal | | 2014 |