DOT-VAE: Disentangling One Factor at a Time. - Vaishnavi Patil; Matthew Evanusa; Joseph F. JáJá (ICANN (1), 2022)

Issues in Sub-Utterance Level Language Identification in a Code Switched Bilingual Scenario. - Jagabandhu Mishra; Joshitha Gandra; Vaishnavi Patil; S. R. Mahadeva Prasanna (SPCOM, 2022)

Deep-Readout Random Recurrent Neural Networks for Real-World Temporal Data. - Matthew Evanusa; Snehesh Shrestha; Vaishnavi Patil; Cornelia Fermüller; Michelle Girvan; Yiannis Aloimonos (SN Comput. Sci., 2022)

t-ConvESN: Temporal Convolution-Readout for Random Recurrent Neural Networks. - Matthew S. Evanusa; Vaishnavi Patil; Michelle Girvan; Joel Goodman; Cornelia Fermüller; Yiannis Aloimonos (ICANN (6), 2023)

ProtoVAE: Prototypical Networks for Unsupervised Disentanglement. - Vaishnavi Patil; Matthew Evanusa; Joseph F. JáJá (CoRR, 2023)

Detecting and Monitoring Bias for Subgroups in Breast Cancer Detection AI. - Amit Kumar Kundu; Florence X. Doo; Vaishnavi Patil; Amitabh Varshney; Joseph F. JáJá (CoRR, 2025)

Boosting Open Set Recognition Performance through Modulated Representation Learning. - Amit Kumar Kundu; Vaishnavi Patil; Joseph F. JáJá (CoRR, 2025)