Aneesh Balakrishnan

Publication Activity (10 Years)

Years Active: 2019-2021
Publications (10 Years): 20

Top Topics

Machine Learning

Inference Engine

Graph Representation

Convolutional Neural Networks

Top Venues

Publications

Aneesh Balakrishnan, Guilherme Cardoso Medeiros, Cemil Cem Gürsoy, Said Hamdioui, Maksim Jenihhin, Dan Alexandrescu
Modeling Soft-Error Reliability Under Variability. DFT (2021)
Aneesh Balakrishnan, Thomas Lange, Maximilien Glorieux, Dan Alexandrescu, Maksim Jenihhin
Composing Graph Theory and Deep Neural Networks to Evaluate SEU Type Soft Error Effects. CoRR (2021)
Aneesh Balakrishnan, Thomas Lange, Maximilien Glorieux, Dan Alexandrescu, Maksim Jenihhin
Modeling Gate-Level Abstraction Hierarchy Using Graph Convolutional Neural Networks to Predict Functional De-Rating Factors. CoRR (2021)
Aneesh Balakrishnan, Dan Alexandrescu, Maksim Jenihhin, Thomas Lange, Maximilien Glorieux
Gate-Level Graph Representation Learning: A Step Towards the Improved Stuck-at Faults Analysis. ISQED (2021)
Dan Alexandrescu, Aneesh Balakrishnan, Thomas Lange, Maximilien Glorieux
Enabling Cross-Layer Reliability and Functional Safety Assessment Through ML-Based Compact Models. CoRR (2021)
Aneesh Balakrishnan, Thomas Lange, Maximilien Glorieux, Dan Alexandrescu, Maksim Jenihhin
The Validation of Graph Model-Based, Gate Level Low-Dimensional Feature Data for Machine Learning Applications. CoRR (2021)
Xinhui Lai, Thomas Lange, Aneesh Balakrishnan, Dan Alexandrescu, Maksim Jenihhin
On Antagonism Between Side-Channel Security and Soft-Error Reliability in BNN Inference Engines. VLSI-SoC (2021)
Thomas Lange, Aneesh Balakrishnan, Maximilien Glorieux, Dan Alexandrescu, Luca Sterpone
Machine Learning to Tackle the Challenges of Transient and Soft Errors in Complex Circuits. CoRR (2020)
Dan Alexandrescu, Aneesh Balakrishnan, Thomas Lange, Maximilien Glorieux
Enabling Cross-Layer Reliability and Functional Safety Assessment Through ML-Based Compact Models. IOLTS (2020)
Aneesh Balakrishnan, Thomas Lange, Maximilien Glorieux, Dan Alexandrescu, Maksim Jenihhin
Composing Graph Theory and Deep Neural Networks to Evaluate SEU Type Soft Error Effects. MECO (2020)
Thomas Lange, Aneesh Balakrishnan, Maximilien Glorieux, Dan Alexandrescu, Luca Sterpone
Machine Learning Clustering Techniques for Selective Mitigation of Critical Design Features. CoRR (2020)
Thomas Lange, Aneesh Balakrishnan, Maximilien Glorieux, Dan Alexandrescu, Luca Sterpone
On the Estimation of Complex Circuits Functional Failure Rate by Machine Learning Techniques. CoRR (2020)
Thomas Lange, Aneesh Balakrishnan, Maximilien Glorieux, Dan Alexandrescu, Luca Sterpone
Machine Learning Clustering Techniques for Selective Mitigation of Critical Design Features. IOLTS (2020)
Maksim Jenihhin, Matteo Sonza Reorda, Aneesh Balakrishnan, Dan Alexandrescu
Challenges of Reliability Assessment and Enhancement in Autonomous Systems. DFT (2019)
Maksim Jenihhin, Matteo Sonza Reorda, Aneesh Balakrishnan, Dan Alexandrescu
Challenges of Reliability Assessment and Enhancement in Autonomous Systems. CoRR (2019)
Aneesh Balakrishnan, Thomas Lange, Maximilien Glorieux, Dan Alexandrescu, Maksim Jenihhin
The Validation of Graph Model-Based, Gate Level Low-Dimensional Feature Data for Machine Learning Applications. NORCAS (2019)
Xinhui Lai, Aneesh Balakrishnan, Thomas Lange, Maksim Jenihhin, Tara Ghasempouri, Jaan Raik, Dan Alexandrescu
Understanding multidimensional verification: Where functional meets non-functional. Microprocess. Microsystems 71 (2019)
Thomas Lange, Aneesh Balakrishnan, Maximilien Glorieux, Dan Alexandrescu, Luca Sterpone
Machine Learning to Tackle the Challenges of Transient and Soft Errors in Complex Circuits. IOLTS (2019)
Aneesh Balakrishnan, Thomas Lange, Maximilien Glorieux, Dan Alexandrescu, Maksim Jenihhin
Modeling Gate-Level Abstraction Hierarchy Using Graph Convolutional Neural Networks to Predict Functional De-Rating Factors. AHS (2019)
Thomas Lange, Aneesh Balakrishnan, Maximilien Glorieux, Dan Alexandrescu, Luca Sterpone
On the Estimation of Complex Circuits Functional Failure Rate by Machine Learning Techniques. DSN (Supplements) (2019)