Narendra Patwardhan

According to our database, Narendra Patwardhan authored at least 10 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

Transformers in the Real World: A Survey on NLP Applications.

Narendra Patwardhan, Stefano Marrone, Carlo Sansone

Inf., April, 2023

VeerNet: Using Deep Neural Networks for Curve Classification and Digitization of Raster Well-Log Images.

M. Quamer Nasim, Narendra Patwardhan, Tannistha Maiti, Stefano Marrone, Tarry Singh

J. Imaging, 2023

Responsible and Reliable AI at PICUS Lab.

Narendra Patwardhan, Lidia Marassi, Michela Gravina, Antonio Galli, Monica Zuccarini, Tannistha Maiti, Tarry Singh, Stefano Marrone, Carlo Sansone

Proceedings of the Italia Intelligenza Artificiale, 2023

Digitizer: A Synthetic Dataset for Well-Log Analysis.

M. Quamer Nasim, Narendra Patwardhan, Javed Ali, Tannistha Maiti, Stefano Marrone, Tarry Singh, Carlo Sansone

Proceedings of the Image Analysis and Processing - ICIAP 2023 Workshops, 2023

Designing Human-Centric Foundation Models.

Narendra Patwardhan, Shreya Shetye, Lidia Marassi, Monica Zuccarini, Tannistha Maiti, Tarry Singh

Proceedings of the First Workshop on User Perspectives in Human-Centred Artificial Intelligence (HCAI4U 2023) co-located with the 15th Biannual Conference of the Italian SIGCHI Chapter (CHItaly 2023), 2023

Can Justice be a measurable value for AI? Proposed evaluation of the relationship between NLP models and principles of Justice.

Lidia Marassi, Narendra Patwardhan, Francesco Gargiulo

Proceedings of the First Workshop on User Perspectives in Human-Centred Artificial Intelligence (HCAI4U 2023) co-located with the 15th Biannual Conference of the Italian SIGCHI Chapter (CHItaly 2023), 2023

2022

Digitization of Raster Logs: A Deep Learning Approach.

M. Quamer Nasim, Narendra Patwardhan, Tannistha Maiti, Tarry Singh

CoRR, 2022

2019

Proximal Reliability Optimization for Reinforcement Learning.

Narendra Patwardhan, Zequn Wang

CoRR, 2019

Reinforcement Learning for Robotics and Control with Active Uncertainty Reduction.

Narendra Patwardhan, Zequn Wang

CoRR, 2019

2018

ARiA: Utilizing Richard's Curve for Controlling the Non-monotonicity of the Activation Function in Deep Neural Nets.

Narendra Patwardhan, Madhura Ingalhalikar, Rahee Walambe

CoRR, 2018