Publications

  1. Vinay Prabhu, John Whaley. SenTenCE: A multi-sensor data compression framework using tensor decompositions for human activity classification. In Proceedings of the Tensor-Learn Workshop, NeurIPS '16, December 10, 2016, Barcelona, Spain.

  2. Vinay Prabhu, Paulo Arantes, John Whaley. Multi-sensor data compression using tensor decompositions: A SenTenCE and more. Poster, NVIDIA GPU Technology Conference (GTC-2017), May 8, 2017, San Jose, California, USA.

  3. Vinay Prabhu, John Whaley. Vulnerability of deep learning-based gait biometric recognition to adversarial perturbations. In Proceedings of the CVPR 2017 CV-COPS workshop, July 21, 2017, Honolulu, Hawaii, USA.

  4. James Bartlett, Vinay Prabhu, John Whaley. AcctionNet: A Dataset Of Human Activity Recognition Using On-phone Motion Sensors. Proceedings of the Time Series Workshop, 34th International Conference on Machine Learning 2017, Sydney, Australia.

  5. Vinay Prabhu, John Whaley. Smile in the face of adversity much? A print-based spoofing attack. In Proceedings of the CVPR 2017 CV-COPS workshop, July 21, 2017, Honolulu, Hawaii, USA.

  6. Aidan Clark, Vinay Uday Prabhu, John Whaley. Weight initialization strategies for Binarized Neural Networks. In Proceedings of the ICML Workshop on TinyML: ML on a Test-time Budget for IoT, Mobiles, and Other Applications, August 10, 2017, Sydney, Australia.

  7. Nikhil Mehta, Vinay Uday Prabhu, John Whaley. Memorization in Binarized Neural Networks. In Proceedings of the ICML Workshop on TinyML: ML on a Test-time Budget for IoT, Mobiles, and Other Applications, August 10, 2017, Sydney, Australia.

  8. Aidan Clark, Vinay Uday Prabhu, John Whaley. A Contextual Discretization framework for compressing Recurrent Neural Networks. Project Report, UnifyID AI fellowship - 2017, https://openreview.net/references/pdf?id=SJGIC1BFe

  9. Vinay Uday Prabhu, John Whaley. On grey-box adversarial attacks and transfer learning. Project Report, Link: https://unify.id/wp-content/uploads/2018/03/greybox_attack.pdf

  10. Vinay Prabhu, John Whaley. On Lyapunov exponents and adversarial perturbations. In Proceedings of the Deep Learning Security Workshop (DLSW-2017), December 15, 2017, Singapore. [Won the Research Forum Best Paper Award $250]

  11. Edgar Minasyan, Vinay Prabhu. Hockey-Stick GAN. Workshop Proceedings, Sixth International Conference on Learning Representations, ICLR-2018, May 2018, Vancouver, Canada.

  12. Vinay Uday Prabhu, John Whaley. Art-attack! On style transfers with textures, label categories, and adversarial examples. In Proceedings of the CVPR 2018 CV-COPS workshop, June 2018, Salt Lake City, Utah, USA.

  13. Vinay Uday Prabhu, Nishant Desai, John Whaley. Chaos Theory meets deep learning: On Lyapunov exponents and adversarial perturbations. In Proceedings of the CVPR 2018 CV-COPS workshop, June 2018, Salt Lake City, Utah, USA.

  14. Vinay Uday Prabhu, Daniel Wen, John Whaley. SIMUni: Sampling Impostors from Misfit Universal Background Models in accelerometric gait biometric verification. Proceedings, BayLearn-18, October 2018, Menlo Park, California, USA.

  15. Vinay Uday Prabhu, Sanghyun Han, Dian Ang Yap, Mihail D, Preethi S. A Seed-Augment-Train framework for universal digit classification. In Proceedings, DGS workshop-ICLR 2019, May 2019, New Orleans, USA. Link: https://arxiv.org/abs/1905.08633

  1. Karttikeya Mangalam, Vinay Uday Prabhu. Do deep neural networks learn shallow learnable examples first? In Proceedings, SPML workshop, ICML-2019, June 2019, Long Beach, California, USA.

  2. Nicholas Roberts, Vinay Uday Prabhu, Matthew McAteer. Model weight theft with just noise inputs: The curious case of the petulant attacker. ICML Security and Privacy of Machine Learning workshop, June 2019, Long Beach, California, USA. (Accepted for spotlight presentation)

  3. Dian Ang Yap, Joyce Xu, Vinay Uday Prabhu, Matthew McAteer. Understanding Adversarial Robustness Through Loss Landscape Geometries. Uncertainty & Robustness in Deep Learning workshop, ICML-2019, June 2019, Long Beach, California, USA.

  4. Vinay Uday Prabhu, Dian Ang Yap, Alex Wang. Covering up bias with Markov blankets: A posthoc cure for attribute prior blindness. Workshop on Invertible Neural Nets and Normalizing Flows, ICML-2019, June 2019, Long Beach, California, USA.

  5. Dian Ang Yap, Joyce Xu, Vinay Uday Prabhu, John Whaley. Detection of Adversarial Inputs through Entropy of Saliency Maps. CVCOPS workshop, CVPR-2019, June 2019, Long Beach, California, USA.

  6. Vinay Prabhu, Stephanie Tietz, Anh Ta. Classifying humans using deep time-series transfer learning: accelerometric gait-cycles to gyroscopic squats. Proceedings, 5th SIGKDD Workshop on Mining and Learning from Time Series (MiLeTS), KDD-2019, August 2019, Anchorage, Alaska. (Accepted as a Contributed Talk.)

  7. Vinay Prabhu, Sangyun Han, John Whaley. Kannada-MNIST: Spurring the MNIST-moment for the numeral scripts in the developing world. Proceedings, ML for the Developing World (ML4D) workshop, NeurIPS-2019, December 2019, Vancouver, Canada.

  8. Dian Ang Yap, Nicholas Roberts, Vinay Uday Prabhu. Grassmannian Packings in Neural Networks: Learning with Maximal Subspace Packings for Diversity and Anti-Sparsity. Proceedings, Workshop on Information Theory and Machine Learning (ITML-2019), NeurIPS-2019, December 2019, Vancouver, Canada.

  9. Nicholas Roberts, Dian Ang Yap, Vinay Uday Prabhu. Deep Connectomics Networks: Neural network architectures inspired by neuronal networks. Proceedings, Neuro-AI Workshop, NeurIPS-2019, December 2019, Vancouver, Canada.

  10. Daniel Wu, Avoy Datta, Vinay Prabhu. BiPedalNet: Binarized Neural Networks for Resource-Constrained On-Device Gait Identification. Proceedings of the Practical ML for Developing Countries Workshop @ ICLR 2020

  11. Daniel J. Wu, Andrew C. Yang, Vinay Prabhu. Afro-MNIST: Synthetic generation of MNIST-style datasets for low-resource languages. Proceedings of the Practical ML for Developing Countries Workshop @ ICLR 2020

  12. Vinay Uday Prabhu, Matthew McAteer. Incorporating structural similarity into neural style transfer. Proceedings, AC-AI workshop, Session 3: Computer Vision, 2020.

  13. Vinay Uday Prabhu, Matthew McAteer. Style transfer with binarized neural networks. Proceedings, AC-AI workshop, Session 3: Computer Vision, 2020.

  14. Vinay Uday Prabhu, Abeba Birhane. Large image datasets: A pyrrhic win for computer vision? Proceedings of 2021 IEEE Winter Conference on Applications of Computer Vision (WACV-2021). arXiv preprint arXiv:2006.16923 (2020).

  15. Vinay Uday Prabhu, Isiain X. A taxonomy of concerns concerning neural art. Proceedings of the CVPR-2021 workshop on ethical considerations in creative applications of computer vision. Video: https://youtu.be/tAea9kJRqcA

  16. Vinay Prabhu and Abeba Birhane. If saliency cropping is the answer, what is the question? Proceedings of the Beyond Fairness CVPR-2021 workshop.

  17. Vinay Prabhu. The phantom of the corpora: JFT-300M. Proceedings of the Beyond Fairness CVPR-2021 workshop.

  18. Abeba Birhane, Vinay Uday Prabhu, and Emmanuel Kahembwe. Multimodal datasets: misogyny, pornography, and malignant stereotypes. arXiv preprint arXiv:2110.01963 (2021).