An Efficient Analog Convolutional Neural Network Hardware Accelerator Enabled by a Novel Memoryless Architecture for Insect-Sized Robots. - Iman Dadras; Mohammad Hasan Ahmadilivani; Saoni Banerji; Jaan Raik; Alvo Aabloo (MOCAST, 2022)

Enhancing Fault Resilience of QNNs by Selective Neuron Splitting. - Mohammad Hasan Ahmadilivani; Mahdi Taheri; Jaan Raik; Masoud Daneshtalab; Maksim Jenihhin (AICAS, 2023)

APPRAISER: DNN Fault Resilience Analysis Employing Approximation Errors. - Mahdi Taheri; Mohammad Hasan Ahmadilivani; Maksim Jenihhin; Masoud Daneshtalab; Jaan Raik (DDECS, 2023)

Analysis and Improvement of Resilience for Long Short-Term Memory Neural Networks. - Mohammad Hasan Ahmadilivani; Jaan Raik; Masoud Daneshtalab; Alar Kuusik (DFT, 2023)

DeepVigor: VulnerabIlity Value RanGes and FactORs for DNNs' Reliability Assessment. - Mohammad Hasan Ahmadilivani; Mahdi Taheri; Jaan Raik; Masoud Daneshtalab; Maksim Jenihhin (ETS, 2023)

Fully-Fusible Convolutional Neural Networks for End-to-End Fused Architecture with FPGA Implementation. - Iman Dadras; Sakineh Seydi; Mohammad Hasan Ahmadilivani; Jaan Raik; Mostafa E. Salehi (ICECS, 2023)

DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators. - Mahdi Taheri; Mohammad Riazati; Mohammad Hasan Ahmadilivani; Maksim Jenihhin; Masoud Daneshtalab; Jaan Raik; Mikael Sjödin; Björn Lisper (ISQED, 2023)

Special Session: Approximation and Fault Resiliency of DNN Accelerators. - Mohammad Hasan Ahmadilivani; Mario Barbareschi; Salvatore Barone; Alberto Bosio; Masoud Daneshtalab; Salvatore Della Torca; Gabriele Gavarini; Maksim Jenihhin; Jaan Raik; Annachiara Ruospo; Ernesto Sánchez 001; Mahdi Taheri (VTS, 2023)

Zero-Memory-Overhead Clipping-Based Fault Tolerance for LSTM Deep Neural Networks. - Bahram Parchekani; Samira Nazari; Mohammad Hasan Ahmadilivani; Ali Azarpeyvand; Jaan Raik; Tara Ghasempouri; Masoud Daneshtalab (DFT, 2024)

Cost-Effective Fault Tolerance for CNNs Using Parameter Vulnerability Based Hardening and Pruning. - Mohammad Hasan Ahmadilivani; Seyedhamidreza Mousavi; Jaan Raik; Masoud Daneshtalab; Maksim Jenihhin (IOLTS, 2024)

Keynote: Cost-Efficient Reliability for Edge-AI Chips. - Maksim Jenihhin; Mahdi Taheri; Natalia Cherezova; Mohammad Hasan Ahmadilivani; Hardi Selg; Artur Jutman; Konstantin Shibin; Anton Tsertov; Sergei Devadze; Rama Mounika Kodamanchili; Ahsan Rafiq; Jaan Raik; et al. (LATS, 2024)

Real-Time Gait Anomaly Detection Using 1D-CNN and LSTM. - Jakob Rostovski; Mohammad Hasan Ahmadilivani; Andrei Krivosei; Alar Kuusik; Muhammad Mahtab Alam (NCDHWS (2), 2024)

Heterogeneous Approximation of DNN HW Accelerators based on Channels Vulnerability. - Natalia Cherezova; Salvatore Pappalardo; Mahdi Taheri; Mohammad Hasan Ahmadilivani; Bastien Deveautour; Alberto Bosio; Jaan Raik; Maksim Jenihhin (VLSI-SoC, 2024)

Special Session: Reliability Assessment Recipes for DNN Accelerators. - Mohammad Hasan Ahmadilivani; Alberto Bosio; Bastien Deveautour; Fernando Fernandes dos Santos; Juan-David Guerrero-Balaguera; Maksim Jenihhin; Angeliki Kritikakou; Robert Limas Sierra; Salvatore Pappalardo; Jaan Raik; Josie E. Rodriguez Condia; Matteo Sonza Reorda; et al. (VTS, 2024)

ProAct: Progressive Training for Hybrid Clipped Activation Function to Enhance Resilience of DNNs. - Seyedhamidreza Mousavi; Mohammad Hasan Ahmadilivani; Jaan Raik; Maksim Jenihhin; Masoud Daneshtalab (CoRR, 2024)

DeepVigor+: Scalable and Accurate Semi-Analytical Fault Resilience Analysis for Deep Neural Network. - Mohammad Hasan Ahmadilivani; Jaan Raik; Masoud Daneshtalab; Maksim Jenihhin (CoRR, 2024)

A Systematic Literature Review on Hardware Reliability Assessment Methods for Deep Neural Networks. - Mohammad Hasan Ahmadilivani; Mahdi Taheri; Jaan Raik; Masoud Daneshtalab; Maksim Jenihhin (ACM Comput. Surv., 2024)