MC-CIM: Compute-in-Memory with Monte-Carlo Dropouts for Bayesian Edge Intelligence

13 November 2021

Papers citing "MC-CIM: Compute-in-Memory with Monte-Carlo Dropouts for Bayesian Edge Intelligence"

8 / 8 papers shown

Title
Neural Precision Polarization: Simplifying Neural Network Inference with Dual-Level Precision Dinithi Jayasuriya Nastaran Darabi Maeesha Binte Hashem A. R. Trivedi MQ 26 1 0 06 Nov 2024
Navigating the Unknown: Uncertainty-Aware Compute-in-Memory Autonomy of Edge Robotics Nastaran Darabi Priyesh Shukla Dinithi Jayasuriya Divake Kumar Alex C. Stutts A. R. Trivedi 22 2 0 30 Jan 2024
Containing Analog Data Deluge at Edge through Frequency-Domain Compression in Collaborative Compute-in-Memory Networks Nastaran Darabi A. R. Trivedi 19 0 0 20 Sep 2023
Conformalized Multimodal Uncertainty Regression and Reasoning Mimmo Parente Nastaran Darabi Alex C. Stutts Theja Tulabandhula A. R. Trivedi UQCV 31 6 0 20 Sep 2023
ADC/DAC-Free Analog Acceleration of Deep Neural Networks with Frequency Transformation Nastaran Darabi Maeesha Binte Hashem Hongyi Pan Ahmet Cetin Wilfred Gomes A. R. Trivedi 16 4 0 04 Sep 2023
Towards Model-Size Agnostic, Compute-Free, Memorization-based Inference of Deep Learning Davide Giacomini Maeesha Binte Hashem Jeremiah Suarez S. Bhunia A. R. Trivedi BDL 13 2 0 14 Jul 2023
Memory-Immersed Collaborative Digitization for Area-Efficient Compute-in-Memory Deep Learning Shamma Nasrin Maeesha Binte Hashem Nastaran Darabi Benjamin Parpillon F. Fahim Wilfred Gomes A. R. Trivedi 13 5 0 07 Jul 2023
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015