Showing 1–17 of 17 results
/ Date/ Name
Aug 26, 2017TraNNsformer: Neural network transformation for memristive crossbar based neuromorphic system designDec 24, 2019PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-efficient ReRAMFeb 20, 2017RESPARC: A Reconfigurable and Energy-Efficient Architecture with Memristive Crossbars for Deep Spiking Neural NetworksJan 29, 2019PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning InferenceJun 11, 2019PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator DesignAug 30, 2025COMET: A Framework for Modeling Compound Operation Dataflows with Explicit CollectivesJul 1, 2018Xcel-RAM: Accelerating Binary Neural Networks in High-Throughput SRAM Compute ArraysDec 7, 2017Incremental Learning in Deep Convolutional Neural Networks Using Partial Network SharingSep 12, 2016FALCON: Feature Driven Selective Classification for Energy-Efficient Image RecognitionJan 30, 2026Unveiling the Potential of Quantization with MXFP4: Strategies for Quantization Error ReductionJun 4, 2019Constructing Energy-efficient Mixed-precision Neural Networks through Principal Component Analysis for Edge IntelligenceMar 15, 2020GENIEx: A Generalized Approach to Emulating Non-Ideality in Memristive Xbars using Neural NetworksJan 23, 2020SPACE: Structured Compression and Sharing of Representational Space for Continual LearningDec 5, 2017An All-Memristor Deep Spiking Neural Computing System: A Step Towards Realizing the Low Power,Stochastic BrainFeb 1, 2019Efficient Hybrid Network Architectures for Extremely Quantized Neural Networks Enabling Intelligence at the EdgeJun 23, 2021NAX: Co-Designing Neural Network and Hardware Architecture for Memristive Xbar based Computing SystemsNov 20, 2017SPARE: Spiking Networks Acceleration Using CMOS ROM-Embedded RAM as an In-Memory-Computation Primitive