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2020 – today
- 2025
[i4]Amit Kumar Kundu, Florence X. Doo, Vaishnavi Patil, Amitabh Varshney, Joseph F. JáJá:
Detecting and Monitoring Bias for Subgroups in Breast Cancer Detection AI. CoRR abs/2502.10562 (2025)- [i3]Amit Kumar Kundu, Vaishnavi Patil, Joseph F. JáJá:
Boosting Open Set Recognition Performance through Modulated Representation Learning. CoRR abs/2505.18137 (2025) - 2023
- [c3]Matthew S. Evanusa, Vaishnavi Patil, Michelle Girvan, Joel Goodman, Cornelia Fermüller, Yiannis Aloimonos:
t-ConvESN: Temporal Convolution-Readout for Random Recurrent Neural Networks. ICANN (6) 2023: 140-151 - [i2]Vaishnavi Patil, Matthew Evanusa, Joseph F. JáJá:
ProtoVAE: Prototypical Networks for Unsupervised Disentanglement. CoRR abs/2305.09092 (2023) - 2022
- [j1]Matthew Evanusa
, Snehesh Shrestha, Vaishnavi Patil, Cornelia Fermüller, Michelle Girvan, Yiannis Aloimonos:
Deep-Readout Random Recurrent Neural Networks for Real-World Temporal Data. SN Comput. Sci. 3(3): 222 (2022) - [c2]Vaishnavi Patil, Matthew Evanusa, Joseph F. JáJá:
DOT-VAE: Disentangling One Factor at a Time. ICANN (1) 2022: 109-120 - [c1]Jagabandhu Mishra, Joshitha Gandra, Vaishnavi Patil, S. R. Mahadeva Prasanna:
Issues in Sub-Utterance Level Language Identification in a Code Switched Bilingual Scenario. SPCOM 2022: 1-5 - [i1]Vaishnavi Patil, Matthew Evanusa, Joseph F. JáJá:
DOT-VAE: Disentangling One Factor at a Time. CoRR abs/2210.10920 (2022)
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