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Tribhuvanesh Orekondy

7 accepted papers

2025

Differentiable and Learnable Wireless Simulation with Geometric Transformers

ICLR 2025poster

Modelling the propagation of electromagnetic wireless signals is critical for designing modern communication systems. Wireless ray tracing simulators model signal propagation based on the 3D geometry and other scene parameters, but their accuracy is fundamentally limited by underlying modelling assu…

Cited by 0SourcePDFScholar
2023

WiNeRT: Towards Neural Ray Tracing for Wireless Channel Modelling and Differentiable Simulations

ICLR 2023poster

In this paper, we work towards a neural surrogate to model wireless electro-magnetic propagation effects in indoor environments. Such neural surrogates provide a fast, differentiable, and continuous representation of the environment and enables end-to-end optimization for downstream tasks (e.g., net…

Cited by 40SourcePDFScholar
2020

GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators

NeurIPS 2020poster

The wide-spread availability of rich data has fueled the growth of machine learning applications in numerous domains. However, growth in domains with highly-sensitive data (e.g., medical) is largely hindered as the private nature of data prohibits it from being shared. To this end, we propose Gradie…

Cited by 215SourcePDFScholar
2020

Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks

ICLR 2020poster

High-performance Deep Neural Networks (DNNs) are increasingly deployed in many real-world applications e.g., cloud prediction APIs. Recent advances in model functionality stealing attacks via black-box access (i.e., inputs in, predictions out) threaten the business model of such applications, which…

Cited by 228SourceScholar
2018

Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images

CVPR 2018poster

Images convey a broad spectrum of personal information. If such images are shared on social media platforms, this personal information is leaked which conflicts with the privacy of depicted persons. Therefore, we aim for automated approaches to redact such private information and thereby protect pr…

2017

Towards a Visual Privacy Advisor: Understanding and Predicting Privacy Risks in Images

ICCV 2017poster

With an increasing number of users sharing information online, privacy implications entailing such actions are a major concern. For explicit content, such as user profile or GPS data, devices (e.g. mobile phones) as well as web services (e.g. facebook) offer to set privacy settings in order to enfor…

Cited by 194PDFScholar