Nimish Shah

发表

The Improved Correlation Matrix Memory (CMML)

Jim Austin, Simon O'Keefe, Nimish Shah, 2007, 2007 International Joint Conference on Neural Networks.

Program Construction: Calculating Implementations from Specifications by R.C. Backhouse, John Wiley & Sons, 2004

Nimish Shah, 2004, J. Funct. Program..

CEPT-a computer-aided manufacturing application for managing equipment reliability and availability in the semiconductor industry

Nimish Shah, Prasad Rampalli, Arakere Ramesh, 1991 .

Runtime Programmable and Memory Bandwidth Optimized FPGA-Based Coprocessor for Deep Convolutional Neural Network

Kuruvilla Varghese, Nimish Shah, Paragkumar Chaudhari, 2018, IEEE Transactions on Neural Networks and Learning Systems.

Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams

Guy Van den Broeck, Wannes Meert, Nimish Shah, 2020, IDA.

Advanced Topics in Term Rewriting by Enno Ohlebusch, Springer Verlag, 2002

Nimish Shah, Nimish Shah, 2006, Journal of Functional Programming.

Technology choices in scaling up sanitation can significantly affect greenhouse gas emissions and the fertiliser gap in India

Nimish Shah, Nicole Unger, Michal Kulak, 2017 .

“Rippling: Meta-Level Guidance for Mathematical Reasoning,” by Alan Bundy, David Basin, Dieter Hutter, and Andrew Ireland, Cambridge University Press, 2005

Nimish Shah, Nimish Shah, 2005, Journal of Automated Reasoning.

Facial Features Classification Using the Temporal Correlation Matrix Memory (TCMML)

Nimish Shah, 2009, 2009 International Conference of Soft Computing and Pattern Recognition.

Scalable hierarchical floorplanning for fast physical prototyping of systems-on-chip

Renshen Wang, Nimish Shah, 2012, ISPD '12.

Knowledge Representation, Reasoning and Declarative Problem Solving by C. Baral, Cambridge University Press, 2003

Nimish Shah, 2004, J. Funct. Program..

PROBLP: A framework for Iow-precision probabilistic inference

Marian Verhelst, Wannes Meert, Nimish Shah, 2019, 2019 56th ACM/IEEE Design Automation Conference (DAC).

On hardware-aware probabilistic frameworks for resource constrained embedded applications

Guy Van den Broeck, Wannes Meert, Nimish Shah, 2019, NeurIPS 2019.

9.4 PIU: A 248GOPS/W Stream-Based Processor for Irregular Probabilistic Inference Networks Using Precision-Scalable Posit Arithmetic in 28nm

Marian Verhelst, Wannes Meert, Nimish Shah, 2021, 2021 IEEE International Solid- State Circuits Conference (ISSCC).

GRAPHOPT: constrained optimization-based parallelization of irregular graphs pdf

Marian Verhelst, Wannes Meert, Nimish Shah, 2021, ArXiv.