Search Results for author: Rohit Singh

Found 9 papers, 2 papers with code

Granger causal inference on DAGs identifies genomic loci regulating transcription

no code implementations ICLR 2022 Alexander P Wu, Rohit Singh, Bonnie Berger

To our knowledge, GrID-Net is the first single-cell analysis tool that accounts for the temporal lag between a genomic locus becoming accessible and its downstream effect on a target gene's expression.

Causal Inference

Consenting to Internet of Things Across Different Social Settings

no code implementations18 Feb 2021 Yasasvi Hari, Rohit Singh, Kizito Nyuytiymbiy, David Butera

Devices connected to the Internet of Things (IoT) are rapidly becoming ubiquitous across modern homes, workplaces, and other social environments.

Cryptography and Security

Ultra-dense Low Data Rate (UDLD) Communication in the THz

no code implementations22 Sep 2020 Rohit Singh, Doug Sicker

Using distributed device-to-device (D2D) communication in the THz, we can cater to these Ultra-dense Low Data Rate (UDLD) type applications.

Multi-agent Reinforcement Learning

MOTH- Mobility-induced Outages in THz: A Beyond 5G (B5G) application

no code implementations13 Nov 2019 Rohit Singh, Douglas Sicker, Kazi Mohammed Saidul Huq

One solution is to maximize the user coverage for a single AP, which might be dependent on multiple parameters.

Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference

no code implementations17 Jan 2019 Xinyu Hu, Paul Szerlip, Theofanis Karaletsos, Rohit Singh

A regression-based BNN model is proposed to predict spatiotemporal quantities like hourly rider demand with calibrated uncertainties.

Time Series Time Series Prediction

Deep Reinforcement Learning for Green Security Games with Real-Time Information

no code implementations6 Nov 2018 Yufei Wang, Zheyuan Ryan Shi, Lantao Yu, Yi Wu, Rohit Singh, Lucas Joppa, Fei Fang

Green Security Games (GSGs) have been proposed and applied to optimize patrols conducted by law enforcement agencies in green security domains such as combating poaching, illegal logging and overfishing.

Q-Learning reinforcement-learning

Designing the Game to Play: Optimizing Payoff Structure in Security Games

no code implementations5 May 2018 Zheyuan Ryan Shi, Ziye Tang, Long Tran-Thanh, Rohit Singh, Fei Fang

We study Stackelberg Security Games where the defender, in addition to allocating defensive resources to protect targets from the attacker, can strategically manipulate the attacker's payoff under budget constraints in weighted L^p-norm form regarding the amount of change.

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