| Unsupervised learning K Tyagi, C Rane, R Sriram, M Manry Artificial intelligence and machine learning for edge computing, 33-52, 2022 | 16 | 2022 |
| Optimizing Performance of Feedforward and Convolutional Neural Networks Through Dynamic Activation Functions C Rane, K Tyagi, M Manry arXiv preprint arXiv:2308.05724, 2023 | 11 | 2023 |
| Automated Sizing and Training of Efficient Deep Autoencoders using Second Order Algorithms K Tyagi, C Rane, M Manry arXiv preprint arXiv:2308.06221, 2023 | 10 | 2023 |
| Optimal Input Gain: All You Need to Supercharge a Feed-Forward Neural Network C Rane, K Tyagi, S Malalur, Y Shinge, M Manry arXiv preprint arXiv:2303.17732, 2023 | 10 | 2023 |
| Regression analysis K Tyagi, C Rane, M Manry Artificial intelligence and machine learning for EDGE computing, 53-63, 2022 | 9 | 2022 |
| Multistage Newton’s Approach for Training Radial Basis Function Neural Networks MM Kanishka Tyagi, Chinmay Rane, Bito Irie SN Computer Science 2 (5, Article 366), 2021 | 8 | 2021 |
| MULTILAYER PERCEPTRON WITH ADAPTIVE ACTIVATION FUNCTIONS CA Rane | 2 | 2016 |
| Dynamic Activations for Neural Net Training C Rane, K Tyagi, T Chugh, N MURALI The Second Tiny Papers Track at ICLR 2024, 2024 | | 2024 |
| Adaptive Activations and Shift Invariance in Shallow Convolutional Neural Networks CA Rane The University of Texas at Arlington, 2021 | | 2021 |
Kanishka TyagiSenior Machine Learning Scientist, Aptiv Corpmavs.uta.edu의 이메일 확인됨
