Tabassum, Anika

6 publications

NeurIPSW 2024 Adapting Segment Anything Model (SAM) to Experimental Datasets via Fine-Tuning on GAN-Based Simulation: A Case Study in Additive Manufacturing Anika Tabassum, Amir Koushyar Ziabari

AAAI 2024 Reinforcement Learning as a Parsimonious Alternative to Prediction Cascades: A Case Study on Image Segmentation Bharat Srikishan, Anika Tabassum, Srikanth Allu, Ramakrishnan Kannan, Nikhil Muralidhar

NeurIPSW 2023 Attention for Causal Relationship Discovery from Biological Neural Dynamics Ziyu Lu, Anika Tabassum, Shruti R. Kulkarn, Lu Mi, J. Nathan Kutz, Eric Todd SheaBrown, Seung-Hwan Lim

NeurIPSW 2022 Li-Ion Battery Material Phase Prediction Through Hierarchical Curriculum Learning Anika Tabassum, Nikhil Muralidhar, Ramakrishnan Kannan, Srikanth Allu

AAAI 2021 DeepCOVID: An Operational Deep Learning-Driven Framework for Explainable Real-Time COVID-19 Forecasting Alexander Rodríguez, Anika Tabassum, Jiaming Cui, Jiajia Xie, Javen Ho, Pulak Agarwal, Bijaya Adhikari, B. Aditya Prakash

AAAI 2021 Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19 Alexander Rodríguez, Nikhil Muralidhar, Bijaya Adhikari, Anika Tabassum, Naren Ramakrishnan, B. Aditya Prakash