Nishad Gothoskar

According to our database, Nishad Gothoskar authored at least 16 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills.

Aidan Curtis, Eric Li, Michael Noseworthy, Nishad Gothoskar, Sachin Chitta, Hui Li, Leslie Pack Kaelbling, Nicole E. Carey

Proceedings of the Forty-second International Conference on Machine Learning, 2025

From pixels to physics: an image-computable model of physical predictions.

Haoliang Wang, Nishad Gothoskar, Joshua B. Tenenbaum, Kevin A. Smith

Proceedings of the 47th Annual Meeting of the Cognitive Science Society, 2025

2024

Partially Observable Task and Motion Planning with Uncertainty and Risk Awareness.

Aidan Curtis, George Matheos, Nishad Gothoskar, Vikash Mansinghka, Joshua B. Tenenbaum, Tomás Lozano-Pérez, Leslie Pack Kaelbling

Proceedings of the Robotics: Science and Systems XX, 2024

2023

Bayes3D: fast learning and inference in structured generative models of 3D objects and scenes.

Nishad Gothoskar, Matin Ghavami, Eric Li, Aidan Curtis, Michael Noseworthy, Karen Chung, Brian Patton, William T. Freeman, Joshua B. Tenenbaum, Mirko Klukas, Vikash K. Mansinghka

CoRR, 2023

3D Neural Embedding Likelihood for Robust Sim-to-Real Transfer in Inverse Graphics.

Guangyao Zhou, Nishad Gothoskar, Lirui Wang, Joshua B. Tenenbaum, Dan Gutfreund, Miguel Lázaro-Gredilla, Dileep George, Vikash K. Mansinghka

CoRR, 2023

3D Neural Embedding Likelihood: Probabilistic Inverse Graphics for Robust 6D Pose Estimation.

Guangyao Zhou, Nishad Gothoskar, Lirui Wang, Joshua B. Tenenbaum, Dan Gutfreund, Miguel Lázaro-Gredilla, Dileep George, Vikash K. Mansinghka

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals.

Alexander K. Lew, George Matheos, Tan Zhi-Xuan, Matin Ghavamizadeh, Nishad Gothoskar, Stuart Russell, Vikash K. Mansinghka

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Solving the Baby Intuitions Benchmark with a Hierarchically Bayesian Theory of Mind.

Tan Zhi-Xuan, Nishad Gothoskar, Falk Pollok, Dan Gutfreund, Joshua B. Tenenbaum, Vikash K. Mansinghka

CoRR, 2022

DURableVS: Data-efficient Unsupervised Recalibrating Visual Servoing via online learning in a structured generative model.

Nishad Gothoskar, Miguel Lázaro-Gredilla, Yasemin Bekiroglu, Abhishek Agarwal, Joshua B. Tenenbaum, Vikash K. Mansinghka, Dileep George

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021

3DP3: 3D Scene Perception via Probabilistic Programming.

Nishad Gothoskar, Marco F. Cusumano-Towner, Ben Zinberg, Matin Ghavamizadeh, Falk Pollok, Austin Garrett, Josh Tenenbaum, Dan Gutfreund, Vikash K. Mansinghka

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables.

Miguel Lázaro-Gredilla, Wolfgang Lehrach, Nishad Gothoskar, Guangyao Zhou, Antoine Dedieu, Dileep George

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Query Training: Learning and inference for directed and undirected graphical models.

Miguel Lázaro-Gredilla, Wolfgang Lehrach, Nishad Gothoskar, Guangyao Zhou, Antoine Dedieu, Dileep George

CoRR, 2020

From proprioception to long-horizon planning in novel environments: A hierarchical RL model.

Nishad Gothoskar, Miguel Lázaro-Gredilla, Dileep George

CoRR, 2020

Learning a generative model for robot control using visual feedback.

Nishad Gothoskar, Miguel Lázaro-Gredilla, Abhishek Agarwal, Yasemin Bekiroglu, Dileep George

CoRR, 2020

2019

Learning higher-order sequential structure with cloned HMMs.

Antoine Dedieu, Nishad Gothoskar, Scott Swingle, Wolfgang Lehrach, Miguel Lázaro-Gredilla, Dileep George

CoRR, 2019

2017

Does this App Really Need My Location?: Context-Aware Privacy Management for Smartphones.

Saksham Chitkara, Nishad Gothoskar, Suhas Harish, Jason I. Hong, Yuvraj Agarwal

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2017