2024
Pirhayati, D., Smith, C.L., Kroeger, R., Navlakha, S., Pfaffinger, P., Reimer, J., Arenkiel, B.R., Patel, A. and Moss, E.H., 2024. Dense and persistent odor representations in the olfactory bulb of awake mice. Journal of Neuroscience, 44(39). Link
Rai, K., Wang, Y., O’Connell, R.W., Patel, A.B. and Bashor, C.J., 2024. Using Machine Learning to Enhance and Accelerate Synthetic Biology. Current Opinion in Biomedical Engineering, p.100553. Link
Chen, Y.H., Lee, J., Zhuang, M., Bi, T., Lagisetty, Y., Singh, S., Velarde, A., Yang, H., Al-Atrash, G., Rondon, G. and Shpall, E., 2024. 3045–MOLECULAR EVOLUTION OF MEASURABLE RESIDUAL DISEASE IN MYELODYSPLASTIC SYNDROMES. Experimental Hematology, 137, p.104367. Link
Caro, J.O., Yilong, J., Pyle, R., Dey, S., Brendel, W., Anselmi, F. and Patel, A.B., 2024. Translational symmetry in convolutions with localized kernels causes an implicit bias toward high frequency adversarial examples. Frontiers in Computational Neuroscience, 18, pp.1-10. Link
Neumann, O., Zhou, J., Ju, Y., Bajomo, M.M., Sánchez-Alvarado, A.B., Dolive, J., Kumela, B., Kumela, M., Patel, A., Nordlander, P. and Halas, N.J., 2024. Surface-Enhanced Raman Spectroscopy: from the Few-Analyte Limit to Hot-Spot Saturation. The Journal of Physical Chemistry C. Link
Ju, Y., Waugh, J.L., Singh, S., Rusin, C.G., Patel, A.B. and Jain, P.N., 2024. A multimodal deep learning tool for detection of junctional ectopic tachycardia in children with congenital heart disease. Heart Rhythm O2. Link
Cimorelli, A., Patel, A., Karakostas, T. and Cotton, R.J., 2024. Validation of portable in-clinic video-based gait analysis for prosthesis users. Scientific Reports, 14(1), p.3840. Link
Singh, S.H., Jiang, K., Bhasin, K., Sabharwal, A., Moukaddam, N. and Patel, A.B., 2024. RACER: An LLM-powered Methodology for Scalable Analysis of Semi-structured Mental Health Interviews. arXiv preprint arXiv:2402.02656. Link
Liang, H., Caro, J.O., Maheshri, V., Patel, A.B. and Balakrishnan, G., 2024. Linking convolutional kernel size to generalization bias in face analysis CNNs. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (pp. 4705-4715). Link
2023
Woodland, M., Taie, M.A., Silva, J.A.M., Eltaher, M., Mohn, F., Shieh, A., Castelo, A., Kundu, S., Yung, J.P., Patel, A.B. and Brock, K.K., 2023. Importance of Feature Extraction in the Calculation of Fr\’echet Distance for Medical Imaging. arXiv preprint arXiv:2311.13717. Link
Charron, N.E., Musil, F., Guljas, A., Chen, Y., Bonneau, K., Pasos-Trejo, A.S., Venturin, J., Gusew, D., Zaporozhets, I., Krämer, A. and Templeton, C., 2023. Navigating protein landscapes with a machine-learned transferable coarse-grained model. arXiv preprint arXiv:2310.18278. Link
Ju, Y., Neumann, O., Bajomo, M., Zhao, Y., Nordlander, P., Halas, N.J. and Patel, A., 2023. Identifying surface-enhanced raman spectra with a raman library using machine learning. ACS nano, 17(21), pp.21251-21261. Link
Woodland, McKell, Nihil Patel, Mais Al Taie, Joshua P. Yung, Tucker J. Netherton, Ankit B. Patel, and Kristy K. Brock. “Dimensionality reduction for improving out-of-distribution detection in medical image segmentation.” In International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, pp. 147-156. Cham: Springer Nature Switzerland, 2023. Link
Xiao, J., Provenza, N.R., Asfouri, J., Myers, J., Mathura, R.K., Metzger, B., Adkinson, J.A., Allawala, A.B., Pirtle, V., Oswalt, D. and Shofty, B., 2023. Decoding depression severity from intracranial neural activity. Biological psychiatry, 94(6), pp.445-453. Link
Lagisetty, Y., Singh, S. and Patel, A., 2023, July. Binding affinity distributions drive adaptation in GRN evolution. In ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference. MIT Press. Link
Woodland, M., O’Connor, C., Wood, J., Patel, A.B. and Brock, K.K., 2023, July. Interpretable Out-of-Distribution Detection with Generative Adversarial Networks. In AAPM 65th Annual Meeting & Exhibition. AAPM. Link
Pyle, R., Musslick, S., Cohen, J.D. and Patel, A.B., 2023. A Quantitative Approach to Predicting Representational Learning and Performance in Neural Networks. arXiv preprint arXiv:2307.07575. Link
Woodland, M., Wood, J., O’Connor, C., Patel, A.B. and Brock, K.K., 2023. StyleGAN2-based Out-of-Distribution Detection for Medical Imaging. arXiv preprint arXiv:2307.10193. Link
Li, Z., Ortega Caro, J., Rusak, E., Brendel, W., Bethge, M., Anselmi, F., Patel, A.B., Tolias, A.S. and Pitkow, X., 2023. Robust deep learning object recognition models rely on low frequency information in natural images. PLOS Computational Biology, 19(3), p.e1010932. Link
2022
Mary Bajomo*, Yilong Ju*, Jingyi Zhou, Simina Elefterescu, Corbin Farr, Yiping Zhao, Oara Neumann, Peter Nordlander, Ankit Patel, Naomi Halas. Detection and Identification of Polycyclic Aromatic Hydrocarbons Using Surface Enhanced Raman Spectroscopy and Effective Characteristic Peak Extraction. PNAS (2022). Link
Yilong Ju*, Shah Saad Alam*, Jonathan Minoff, Fabio Anselmi, Han Pu, Ankit Patel. Interpreting Convolutional Neural Networks’ Low Dimensional Approximation to Quantum Spin Systems. Link
Jiayang Xiao, Nicole R. Provenza, Joseph Asfouri, John Myers, Raissa K. Mathura, Brian Metzger, Joshua A. Adkinson, Anusha B. Allawala, Victoria Pirtle, Denise Oswalt, Ben Shofty, Meghan E. Robinson, Sanjay J. Mathew, Wayne K. Goodman, Nader Pouratian, Paul R. Schrater, Ankit B. Patel, Andreas S. Tolias, Kelly R. Bijanki, Xaq Pitkow, Sameer A. Sheth. Decoding Depression Severity from Intracranial Neural Activity. Biological Psychiatry (2023) Link
R. James Cotton*, Emoonah McClerklin, Anthony Cimorelli, Ankit Patel, Tasos Karakostas. Transforming Gait: Video-Based Spatiotemporal Gait Analysis. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). Link
Justin Sahs, Ryan Pyle, Aneel Damaraju, Josue Ortega Caro, Onur Tavaslioglu, Andy Lu, Fabio Anselmi, Ankit Patel. Shallow Univariate ReLu Networks as Splines: Initialization, Loss Surface, Hessian, & Gradient Flow Dynamics. Frontiers in Artificial Intelligence (2022) as part of a Special Issue on Symmetry in Deep Learning. Link
Bishal Lamichhane, Nidal Moukaddam, Ankit B. Patel and Ashutosh Sabharwal. ECoNet: Estimating Everyday Conversational Network From Free-Living Audio for Mental Health Applications. To appear in IEEE Pervasive Computing (2022).
Jamie L.S. Waugh, Raajen Patel, Yilong Ju, Ankit Patel, Craig Rusin, Parag Jain. A Novel Automated Junctional Ectopic Tachycardia Detection Tool for Children with Congenital Heart Disease. Heart Rhythm O2 (2022). doi: https://doi.org/10.1016/j.hroo.2022.02.014
Zhe Li, Josue Ortega Caro, Evgenia Rusak, Wieland Brendel, Matthias Bethge, Fabio Anselmi, Ankit B Patel, Andreas Tolias, Xaq Pitkow. Robust Deep Learning Object Recognition Models Rely on Low Frequency Information in Natural Images. bioRxiv 2022.01.31.478509; doi: https://doi.org/10.1101/2022.01.31.478509
2021
Wenwan Chen, Ashutosh Sabharwal, Erica Taylor, Ankit B. Patel and
Nidal Moukaddam. Privacy-preserving Social Ambiance Measure
from Free-living Speech Associates with
Chronic Depressive and Psychotic Disorders. Frontiers in Psychiatry (2021).
Jiangguo Zhang, Jessica A. Comstock, Christopher R. Cotter, Patrick A. Murphy, Weili Nie, Roy D. Welch, Ankit B. Patel, Oleg A. Igoshin. Quantification of Myxococcus Xanthus Aggregation and Rippling Behaviors: Deep-learning Transformation of Phase-contrast into Fluorescence Microscopy Images. Microorganisms (2021). bioRxiv 2021.07.16.452736; doi: https://doi.org/10.1101/2021.07.16.452736
Ryan Pyle, Nikola Jovanovic, Devika Subramanian, Krishna V. Palem and Ankit B. Patel. Domain-Driven Models Yield Better Predictions at Lower Cost than Reservoir Computers in Lorenz Systems. Philosophical Transactions of the Royal Society A 379: 20200246.
https://doi.org/10.1098/rsta.2020.0246
Justin Sahs, Ryan Pyle, Aneel Damaraju, Josue Ortega Caro, Onur Tavaslioglu, Andy Lu, Ankit Patel (2020-2021). Shallow Univariate ReLu Networks as Splines: Initialization, Loss Surface, Hessian, & Gradient Flow Dynamics. ArXiv
Josue Ortega Caro, Yilong Ju, Fabio Anselmi, Sourav Dey, Ryan Pyle, Ankit Patel (2020-2021). Using Learning Dynamics to Explore the Role of Implicit Regularization in Adversarial Examples. ArXiv
2020
Weili Nie, Zhiding Yu, Lei Mao, Ankit B. Patel, Yuke Zhu, Anima Anandkumar. Bongard-LOGO: A new benchmark for human-level concept learning and reasoning. Advances in Neural Information Processing Systems (NeurIPS), 2020 (Spotlight) ArXiv / code / slides Anselmi, Fabio, Patel, Ankit B. & Rosasco, L. Neurally Plausible Mechanisms for Learning Selective and Invariant Representations. J. Math. Neurosc. 10, 12 (2020). https://doi.org/10.1186/s13408-020-00088-7 Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit B. Patel, Anima Anandkumar (2020). Semi-Supervised StyleGAN for Disentanglement Learning. International Conference in Machine Learning (ICML). ArXiv ICML NVIDIA Project Page Li Yang, Zhaoqi Leng, Guangyuan Yu, Ankit Patel, Wen-Jun Hu, Han Pu (2019). Deep Learning-Enhanced Variational Monte Carlo Method for Quantum Many-Body Physics. Physical Review Research, 2020. PRR ArXiv |
2018-2019
| Huaijin Chen, Wanjia Liu, Rhonald Lua, Rishab Goel, Yuzhong Huang, Ashok Veeraraghavan, Ankit Patel (2019). Fast Retinomorphic Event-Driven Representations for Video Gameplay and Action Recognition. IEEE Transactions in Computational Imaging, 2019. ArXiv IEEE TCI N. Ho, T. Nguyen, A. B. Patel, A. Anandkumar, M. I. Jordan, R. G. Baraniuk. Neural Rendering Model: Joint Generation and Prediction for Semi-Supervised Learning. DeepMath 2019.N. Ho, T. Nguyen, A. B. Patel, A. Anandkumar, M. I. Jordan, R. G. Baraniuk. The Latent-Dependent Deep Rendering Model. Workshop on Theoretical Foundations and Applications of Deep Generative Models at ICML, 2018Li Yang, Zhaoqi Leng, Guangyuan Yu, Ankit Patel, Wen-Jun Hu, Han Pu (2019). Deep Learning-Enhanced Variational Monte Carlo Method for Quantum Many-Body Physics. ArXiV, 2019. ArXiV Weili Nie, Ankit B. Patel (2019). Towards A Better Understanding and Regularization of GAN Training Dynamics. UAI 2019. Joshua J. Michalenko, Ameesh Shah, Abhinav Verma, Swarat Chaudhuri, Ankit B. Patel (2019). Finite Automata Can be Linearly Decoded from Language-Recognizing RNNs. International Conference on Learning Representations (ICLR), 2019. ICLR pdf Weili Nie, Nina Narodytska, Ankit Patel (2019). RelGAN: Relational Generative Adversarial Networks for Text Generation. International Conference on Learning Representations (ICLR), 2019. ICLR pdf Weili Nie, Yang Zhang, Ankit Patel (2018). A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations. Proceedings of the International Conference of Machine Learning (ICML), PMLR 80:3809-3818, 2018. ICML ArXiV pdf | |
| Huaijin Chen, Wanjia Liu, Rishab Goel, Yuzhong Huang, Ashok Veeraraghavan, Ankit Patel (2018). EDR: Retinomorphic Event-Driven Representations for Motion Vision. IEEE International Conference on Computational Photography,. |
2016
| Tan Nguyen, Richard Baraniuk, Ankit Patel (2016). Semi-Supervised Learning with the Deep Rendering Mixture Model. ArXiV pdf | |
| Ankit Patel, Tan Nguyen, Richard Baraniuk (2016). A Probabilistic Framework for Deep Learning. NIPS 2016, Barcelona, Spain. pdf NIPS | |
| Gavin Taylor, Ryan Burmeister, Zheng Xu, Bharat Singh, Ankit Patel, Tom Goldstein (2016). Training Neural Networks without Gradients: A Scalable ADMM Approach. ICML 2016, New York City USA. ICML ArXiV | |
| (2016). A Probabilistic Theory of Deep Learning. Cosyne Abstracts 2016, Salt Lake City USA. |
2015
| (2015). A Deep Learning Approach to Structured Signal Recovery. 53rd Annual Allerton Conference on Communication, Control, and Computing, Sept 29-Oct 2, 2015, Allerton Park and Retreat Center, Monticello, IL, USA. | |
| A Probabilistic Theory of Deep Learning. No. 2015-1: Rice University, Department of Electrical and Computer Engineering, Mar. 15, 2015. arXiv |
2008-2012
All research during this period was proprietary.
2003 – 2007
| The Emergence of Geometric Order in Proliferating Metazoan Epithelia. Matthew Gibson*, Ankit Patel*, Radhika Nagpal, Norbert Perrimon. Nature 42, pp. 1038-1041. Aug 31, 2006. *co-first authors | |
| Desynchronization: A self-organizing algorithm for desynchronization and periodic resource scheduling. Ankit Patel, Julius Degesys, Radhika Nagpal. IEEE International Conference on Self-Adaptive and Self-Organizing Systems, July 2007. | |
| DESYNC: Self-organizing Desynchronization and TDMA on Wireless Sensor Networks. Julius Degesys, Ian Rose, Ankit Patel, Radhika Nagpal. International Conference on Information Processing in Sensor Networks, April 2007. | |
| Firefly-Inspired Sensor Network Synchronicity with Realistic Radio Effects. Geoff Werner-Allen, Geetika Tewari, Ankit Patel, Matt Welsh, Radhika Nagpal. In the ACM Conference on Embedded Networked Sensor Systems (SenSys’05), November 2005. | |
| Determining the Optimal Time for Feature Aided Track Correlation Between Two Radars, [U]. Ankit Patel, Matthew Smith, Keh-Ping Dunn. In Conference on Missile Defense: Sensors, Environments, Architectures, November 2003. |
Ankit Patel's Lab 