Improving Neural Text Style Transfer by Introducing Loss Function Sequentiality. - Chinmay Rane; Gaël Dias; Alexis Lechervy; Asif Ekbal (SIGIR, 2021)

Multistage Newton's Approach for Training Radial Basis Function Neural Networks. - Kanishka Tyagi; Chinmay Rane; Bito Irie; Michael T. Manry (SN Comput. Sci., 2021)

A novel attention fusion network-based framework to ensemble the predictions of CNNs for lymph node metastasis detection. - Chinmay Rane; Raj Mehrotra; Shubham Bhattacharyya; Mukta Sharma; Mahua Bhattacharya (J. Supercomput., 2021)

Optimal Input Gain: All You Need to Supercharge a Feed-Forward Neural Network. - Chinmay Rane; Kanishka Tyagi; Sanjeev S. Malalur; Yash Shinge; Michael T. Manry (CoRR, 2023)

Optimizing Performance of Feedforward and Convolutional Neural Networks through Dynamic Activation Functions. - Chinmay Rane; Kanishka Tyagi; Michael T. Manry (CoRR, 2023)

Dynamic Activations for Neural Net Training. - Chinmay Rane; Kanishka Tyagi; Tushar Chugh; Nirmala Murali (Tiny Papers @ ICLR, 2024)

Making Sigmoid-MSE Great Again: Output Reset Challenges Softmax Cross-Entropy in Neural Network Classification. - Kanishka Tyagi; Chinmay Rane; Ketaki Vaidya; Jeshwanth Challagundla; Soumitro Swapan Auddy; Michael T. Manry (CoRR, 2024)

Optimizing performance of feedforward and convolutional neural networks through dynamic activation functions. - Chinmay Rane; Kanishka Tyagi; Adrienne Kline; Tushar Chugh; Michael T. Manry (Evol. Intell., 2024)