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Making the invisible visible–inside our bodies, around us, and beyond–for health, work, and connection

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Camera Culture

Camera Culture

Publication

Decentralized AI Roundtable 2 - August 20, 2024

Publication

Split Inference - Metrics, Benchmarks and Algorithms

Abhishek Singh, Split Inference - Metrics, Benchmarks and Algorithms, ECCV'24

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DecentNeRFs: Decentralized Neural Radiance Fields from Crowdsourced Images

Zaid Tasneem, DecentNeRFs: Decentralized Neural Radiance Fields from Crowdsourced Images, ECCV'24

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Handheld Mapping of Specular Surfaces using Consumer-grade Flash Lidar.

Tsung-Han Lin, Connor Henley, Siddharth Somasundaram, Akshat Dave, Moshe Laifenfeld, and Ramesh Raskar. Handheld mapping of specular surfaces using consumer-grade flash lidar. In IEEE International Conference on Computational Photography (ICCP), 2024.

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Decentralized AI Round Table 1: July 29, 2024

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A Perspective on Decentralizing AI

Whitepaper

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PlatoNeRF: 3D Reconstruction in Plato's Cave via Single-View Two-Bounce Lidar

Klinghoffer, Tzofi, et al. "PlatoNeRF: 3D Reconstruction in Plato's Cave via Single-View Two-Bounce Lidar." IEEE Conference on Computer Vision and Pattern Recognition (2024).

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flame: A Framework for Learning in Agent-based ModEls

Chopra, Ayush, et al. "flame: A Framework for Learning in Agent-based ModEls." Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems. 2024.

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Posthoc privacy guarantees for collaborative inference

Singh, Abhishek, et al. "Posthoc privacy guarantees for collaborative inference with modified Propose-Test-Release." Advances in Neural Information Processing Systems 36 (2024).

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Posthoc privacy guarantees for collaborative inference with modified Propose-Test-Release

Singh, Abhishek, et al. "Posthoc privacy guarantees for collaborative inference with modified Propose-Test-Release." Thirty-seventh Conference on Neural Information Processing Systems. 2023.

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DiSER: Designing Imaging Systems with Reinforcement Learning

Klinghoffer, Tzofi, et al. "DISeR: Designing Imaging Systems with Reinforcement Learning." Proceedings of the IEEE/CVF International Conference on Computer Vision. 2023.

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Federated Conformal Predictors for Distributed Uncertainty Quantification

Lu, C.*, Yu, Y.*, Karimireddy, S. P., Jordan, M. I., & Raskar, R. (2023). Federated Conformal Predictors for Distributed Uncertainty Quantification. Fortieth International Conference on Machine Learning (ICML 2023)

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Conformal Prediction with Large Language Models for Multi-Choice Question Answering

Kumar, B.*, Lu, C.*, Gupta, G., Palepu, A., Bellamy, D., Raskar, R., & Beam, A. "Conformal Prediction with Large Language Models for Multi-Choice Question Answering." Neural Conversational AI Workshop at ICML 2023.

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Splintering: A resource-efficient and private scheme for distributed matrix inverse

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Parallel quasi-concave set function optimization for scalability even without submodularity

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ORCa: Glossy Objects as Radiance-Field Cameras

Kushagra Tiwary, Akshat Dave, Nikhil Behari, Tzofi Klinghoffer, Ashok Veeraraghavan, Ramesh Raskar. "ORCa: Glossy Objects as Radiance-Field Cameras." Conference on Computer Vision and Pattern Recognition.

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Detection and Mapping of Specular Surfaces Using Multibounce Lidar Returns

Connor Henley, Siddharth Somasundaram, Joseph Hollmann, and Ramesh Raskar, "Detection and mapping of specular surfaces using multibounce LiDAR returns," Opt. Express 31, 6370-6388 (2023).

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Formal privacy guarantees for neural network queries by estimating local Lipschitz constant

Formal Privacy Guarantees for Neural Network queries by estimating local Lipschitz constant

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Private independence testing across two parties

Private independence testing across two parties

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Effects of Privacy-Inducing Noise on Welfare and Influence of Referendum Systems

Suat Evren, Praneeth Vepakomma

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NoPeek-Infer: Preventing face reconstruction attacks in distributed inference after on-premise training

Praneeth Vepakomma, Abhishek Singh, Emily Zhang, Otkrist Gupta, Ramesh Raskar, IEEE International Conference on Automatic Face and Gesture Recognition (FG) 2021

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Private measurement of nonlinear correlations between data hosted across multiple parties

Praneeth Vepakomma, Subha Nawer Pushpita, Ramesh Raskar

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NoPeek-Infer: Preventing face reconstruction attacks in distributed inference after on-premise training

NoPeek-Infer: Preventing face reconstruction attacks in distributed inference after on-premise training

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ZFlow: Gated Appearance Flow-based Virtual Try-on with 3D Priors

Ayush Chopra, Rishabh Jain, Mayur Hemani, Balaji Krishnamurthy. "ZFlow: Gated Appearance Flow-based Virtual Try-on with 3D Priors". International Conference on Computer Vision (ICCV) 2021

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Objects As Cameras: Estimating High-Frequency Illumination From Shadows

Tristan Swedish, Connor Henley, Ramesh Raskar; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021, pp. 2593-2602

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AirMixML: Over-the-Air Data Mixup for Inherently Privacy-Preserving Edge Machine Learning

IEEE Global Communications Conference (GLOBECOM), 2021

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Differentially Private Supervised Manifold Learning with Applications like Private Image Retrieval

Vepakomma, Praneeth et al. Differentially Private Supervised Manifold Learning with Applications like Private Image Retrieval. arXiv:2102.10802v1 [cs.LG] 22 Feb 2021

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FedML: A Research Library and Benchmark for Federated Machine Learning

Chaoyang He, Songze Li, Jinhyun So, Mi Zhang, Xiao Zeng, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, Xinghua Zhu, Jianzong Wang, Li Shen, Peilin Zhao, Yan Kang, Yang Liu, Ramesh Raskar, Qiang Yang, Murali Annavaram and Salman Avestimehr. "FedML: A Research Library and Benchmark for Federated Machine Learning." NeurIPS-SpicyFL 2020. (Baidu Best Paper Award)

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DAMS: Meta-estimation of private sketch data structures for differentially private COVID-19 contact tracing

DAMS: Meta-estimation of private sketch data structures for differentially private COVID-19 contact tracing, Praneeth Vepakomma, Subha Nawer Pushpita and Ramesh Raskar, PPML (Privacy Preserving Machine Learning workshop) at NeurIPS

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DISCO: Dynamic and Invariant Sensitive Channel Obfuscation

Abhishek Singh, Ayush Chopra, Praneeth Vepakomma, Ethan Z Garza, Vivek Sharma, , Ramesh Raskar. "DISCO: Dynamic and Invariant Sensitive Channel Obfuscation." CVPR 2021

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Imaging Behind Occluders Using Two-Bounce Light

Henley, C., Maeda, T., Swedish, T., & Raskar, R. (2020). Imaging Behind Occluders Using Two-Bounce Light. Computer Vision – ECCV 2020 Lecture Notes in Computer Science, 573-588. doi:10.1007/978-3-030-58526-6_34

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Splintering with distributions: A stochastic decoy scheme for private computation

Vepakomma, P., Balla, J., Raskar, R., "Splintering with distributions: A stochastic decoy scheme for private computation." 6 Jul 2020.

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Advances and Open Problems in Federated Learning

Peter Kairouz, H. Brendan McMahan, et al. "Advances and Open Problems in Federated Learning." arXiv:1912.04977 [cs.LG] 10 Dec 2019.

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ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations

Vivek Sharma, Praneeth Vepakomma, Tristan Swedish, Ken Chang, Jayashree KalpathyCramer, and Ramesh Raskar. In NeurIPS Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness, and Privacy, 2019

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Maximal adversarial perturbations for obfuscation: Hiding certain attributes while preserving rest

Indu Ilanchezian, Praneeth Vepakomma, Abhishek Singh, Otkrist Gupta, GN Prasanna, Ramesh Raskar

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ExpertMatcher: Automating ML Model Selection for Users in Resource Constrained Countries

Vivek Sharma, Praneeth Vepakomma, Tristan Swedish, Ken Chang, Jayashree Kalpathy-Cramer, Ramesh Raskar. In NeurIPS Workshop on Machine learning for the Developing World (ML4D), 2019

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Detailed comparison of communication efficiency of split learning and federated learning,

Praneeth Vepakomma, et al. "Detailed comparison of communication efficiency of split learning and federated learning." arXiv:1909.09145v1 [cs.LG] 18 Sep 2019.

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Diverse data selection via combinatorial quasi-concavity of distance covariance: A polynomial time global minimax algorithm

Diverse data selection via combinatorial quasi-concavity of distance covariance: A polynomial time global minimax algorithm, Praneeth Vepakomma, Yulia Kempner

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Data Markets to support AI for All: Pricing, Valuation and Governance

Ramesh Raskar, Praneeth Vepakomma, Tristan Swedish, Aalekh Sharan. Data Markets to support AI for All: Pricing, Valuation and Governance, arXiv:1905.06462 (2019).

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Reducing leakage in distributed deep learning for sensitive health data

Praneeth Vepakomma, Otkrist Gupta, Abhimanyu Dubey, Ramesh Raskar. Reducing Leakage in Distributed Deep Learning for Sensitive Health Data, ICLR 2019 AI for Social Good Workshop (2019).

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Light-Field for RF

Light-Field for RF. Manikanta Kotaru, Guy Satat, Ramesh Raskar, Sachin Katti, arXiv:1901.03953 (2019).

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A Review of Homomorphic Encryption Libraries for Secure Computation

Sai Sri Sathya, Praneeth Vepakomma, Ramesh Raskar, Ranjan Ramachandra, Santanu Bhattacharya. arXiv:1812.02428

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Split learning for health: Distributed deep learning without sharing raw patient data

Praneeth Vepakomma, Otkrist Gupta, Tristan Swedish, Ramesh Raskar. Split learning for health: Distributed deep learning without sharing raw patient data, arXiv.org, ICLR 2019 AI for Social Good Workshop (2018).

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Flash Photography for Data-Driven Hidden Scene Recovery

Flash Photography for Data-Driven Hidden Scene Recovery. Matthew Tancik, Guy Satat, Ramesh Raskar, arXiv:1810.11710 (2018).

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Photography optics in the time dimension

Heshmat, B., Tancik, M., Satat, G. & Raskar, R. Photography optics in the time dimension. Nature Photonics 12, 560–566 (2018). 10.1038/s41566-018-0234-0

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Towards Photography Through Realistic Fog

G. Satat, M. Tancik and R. Raskar, "Towards Photography Through Realistic Fog", IEEE International Conference on Computational Photography (ICCP), (2018).

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Rethinking Machine Vision Time of Flight With GHz Heterodyning

Kadambi, Achuta and Raskar, Ramesh, Rethinking Machine Vision Time of Flight with GHz Heterodyning, IEEE Access 2017

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Calibration Invariant Imaging with Deep Learning

Guy Satat, Matthew Tancik, Otkrist Gupta, Barmak Heshmat, and Ramesh Raskar, "Object classification through scattering media with deep learning on time resolved measurement," Opt. Express 25, 17466-17479 (2017)

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Polarized 3D Cameras for high-quality 3D scanning

Kadambi, Achuta, et al. "Depth Sensing Using Geometrically Constrained Polarization Normals." International Journal of Computer Vision 125.1-3 (2017): 34-51.

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Zensei: Embedded, Multi-electrode Bioimpedance Sensing for Implicit, Ubiquitous User Recognition

Munehiko Sato, Rohan S. Puri, Alex Olwal, Yosuke Ushigome, Lukas Franciszkiewicz, Deepak Chandra, Ivan Poupyrev, and Ramesh Raskar. 2017. Zensei: Embedded, Multi-electrode Bioimpedance Sensing for Implicit, Ubiquitous User Recognition. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17). ACM, New York, NY, USA, 3972-3985.

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Femto-Photography: Capturing Light in Motion

A Jarabo, B Masia, A Velten, R Raskar, D Gutiérrez Jornada de Jóvenes Investigadores del I3A, 2017

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Designing Neural Network Architectures using Reinforcement Learning

Bowen Baker, Otkrist Gupta, Nikhil Naik, Ramesh Raskar arXiv preprint arXiv:1611.02167

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LRA: Local Rigid Averaging of Stretchable Non-rigid Shapes

Raviv, D., Bayro-Corrochano, E. & Raskar, R. Int J Comput Vis (2017). doi:10.1007/s11263-017-1002-1

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Lensless Imaging with Compressive Ultrafast Sensing

Guy Satat, Matthew Tancik, Ramesh Raskar 10.1109/TCI.2017.2684624

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Sampling Without Time: Recovering Echoes of Light via Temporal Phase Retrieval

Ayush Bhandari, Aurelien Bourquard, Ramesh Raskar 12 pages, 4 figures, to appear at the 42nd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

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32 Image Processing in Medical Imaging

Anshuman J Das, Ramesh Raskar Global Health Informatics: Principles of Ehealth and Mhealth to Improve Quality of Care, page 403