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rachmad's Projects

accelat icon accelat

A Framework for Accelerating the Adversarial Training of Deep Neural Networks through Accuracy Gradient

accelerator-wall icon accelerator-wall

Repository for the tools and non-commercial data used for the "Accelerator wall" paper.

adanet icon adanet

Fast and flexible AutoML with learning guarantees.

adapt icon adapt

Fast Emulation of Approximate DNN Accelerators in PyTorch

ai-chip icon ai-chip

A list of ICs and IPs for AI, Machine Learning and Deep Learning.

aihwkit icon aihwkit

IBM Analog Hardware Acceleration Kit

akida_examples icon akida_examples

Brainchip Akida Neuromorphic System-on-Chip examples and documentation.

amc icon amc

[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices

amc-models icon amc-models

[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices

analognas icon analognas

Analog AI Neural Architecture Search (analog-nas) is a modular and flexible framework to facilitate implementation of Analog-aware Neural Architecture Search.

ann_continual_learning icon ann_continual_learning

PyTorch implementation of various methods for continual learning (XdG, EWC, online EWC, SI, LwF, GR, GR+distill, RtF, ER, A-GEM, iCaRL).

annette icon annette

ANNETTE - Accurate Neural Network Execution Time Estimation

apq icon apq

[CVPR 2020] APQ: Joint Search for Network Architecture, Pruning and Quantization Policy

ares icon ares

Ares: A framework for quantifying the resilience of deep neural networks

asa-snn icon asa-snn

Offical implementation of "Inherent Redundancy in Spiking Neural Networks" (ICCV2023)

attentionsnn icon attentionsnn

Offical implementation of "Attention Spiking Neural Networks" (IEEE T-PAMI2023)

auryn icon auryn

Auryn: A fast simulator for spiking neural networks with synaptic plasticity

autosnn icon autosnn

Official code of "AutoSNN: Towards Energy-Efficient Spiking Neural Networks," ICML22

avalanche icon avalanche

Avalanche: a End-to-End Library for Continual Learning

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