activity
20132021
most citedA Multi-objective Perspective for Operator Scheduling using Fine-grained DVS Architecture

2 citations · 2 across the 3 of their papers we have counts for

collaborators

8 papers

cs.FL2021

Methodology for Biasing Random Simulation for Rapid Coverage of Corner Cases in AMS Designs

Sayandeep Sanyal, Ayan Chakraborty, Pallab Dasgupta +1

Exploring the limits of an Analog and Mixed Signal (AMS) circuit by driving appropriate inputs has been a serious challenge to the industry. Doing an exhaustive search of the entir…

cs.AI2021

Hierarchical Program-Triggered Reinforcement Learning Agents For Automated Driving

Briti Gangopadhyay, Harshit Soora, Pallab Dasgupta

Recent advances in Reinforcement Learning (RL) combined with Deep Learning (DL) have demonstrated impressive performance in complex tasks, including autonomous driving. The use of…

cs.FL2020

Quantitative Corner Case Feature Analysis of Hybrid Automata with ForFET

Antonio Anastasio Bruto da Costa, Pallab Dasgupta, Nikolaos Kekatos

The analysis and verification of hybrid automata (HA) models against rich formal properties can be a challenging task. Existing methods and tools can mainly reason whether a given…

cs.FL2020

Recurrence in Dense-time AMS Assertions

Sayandeep Sanyal, Antonio Anastasio Bruto da Costa, Pallab Dasgupta

The notion of recurrence over continuous or dense time, as required for expressing Analog and Mixed-Signal (AMS) behaviours, is fundamentally different from what is offered by the…

eess.SY2020

Early-Stage Resource Estimation from Functional Reliability Specification in Embedded Cyber-Physical Systems

Ginju V. George, Aritra Hazra, Pallab Dasgupta +1

Reliability and fault tolerance are critical attributes of embedded cyber-physical systems that require a high safety-integrity level. For such systems, the use of formal functiona…

cs.AI2020

Semi-Lexical Languages -- A Formal Basis for Unifying Machine Learning and Symbolic Reasoning in Computer Vision

Briti Gangopadhyay, Somnath Hazra, Pallab Dasgupta

Human vision is able to compensate imperfections in sensory inputs from the real world by reasoning based on prior knowledge about the world. Machine learning has had a significant…