tinyML Talks: A Practical Guide to Neural Network Quantization
tinyML Talks: A Practical Guide to Neural Network Quantization
|
Yükleniyor...
Lütfen bekleyiniz...
Type
Size

 İlgili Videolar

tinyML Talks: A Practical Guide to Neural Network Quantization

tinyML Talks: A Practical Guide to Neural Network Quantization

|
tinyML Talks: From the lab to the edge: Post-Training Compression

tinyML Talks: From the lab to the edge: Post-Training Compression

|
Downsizing Neural Networks by Quantization - Introduction to Deep Learning

Downsizing Neural Networks by Quantization - Introduction to Deep Learning

|
tinyML Talks: Low Precision Inference and Training for Deep Neural Networks

tinyML Talks: Low Precision Inference and Training for Deep Neural Networks

|
tinyML Talks France: How to design a power frugal hardware for AI - the bio-inspiration path

tinyML Talks France: How to design a power frugal hardware for AI - the bio-inspiration path

|
tinyML Talks Kristofor Carlson: The Akida Neural Processor: Low Power CNN Inference and Learning...

tinyML Talks Kristofor Carlson: The Akida Neural Processor: Low Power CNN Inference and Learning...

|
tinyML Talks local Germany Marcus Rueb: Introduction to optimization algorithms to compress neural..

tinyML Talks local Germany Marcus Rueb: Introduction to optimization algorithms to compress neural..

|
tinyML EMEA - Mart van Baalen: Advances in quantization for efficient on-device inference

tinyML EMEA - Mart van Baalen: Advances in quantization for efficient on-device inference

|
tinyML Talks Lukas Geiger: Binarized Neural Networks on microcontrollers

tinyML Talks Lukas Geiger: Binarized Neural Networks on microcontrollers

|
ZeroQ: A Novel Zero Shot Quantization Framework

ZeroQ: A Novel Zero Shot Quantization Framework

|
tinyML Research Symposium 2021 Poster: TENT: Efficient Quantization of Neural Networks on the tiny..

tinyML Research Symposium 2021 Poster: TENT: Efficient Quantization of Neural Networks on the tiny..

|
tinyML Research Symposium 2021: Quantization-Guided Training for Compact TinyML Models

tinyML Research Symposium 2021: Quantization-Guided Training for Compact TinyML Models

|
Neural network quantization with AdaRound

Neural network quantization with AdaRound

|
tinyML Talks Martino Sorbaro: Always-on visual classification below 1 mW with spiking...

tinyML Talks Martino Sorbaro: Always-on visual classification below 1 mW with spiking...

|
tinyML Asia 2020 Kai YU: Structured Quantization for Neural Network Language Model Compression

tinyML Asia 2020 Kai YU: Structured Quantization for Neural Network Language Model Compression

|
GTC 2021: Systematic Neural Network Quantization

GTC 2021: Systematic Neural Network Quantization

|
tinyML Asia 2021 Dongsoo Lee: Extremely low-bit quantization for Transformers

tinyML Asia 2021 Dongsoo Lee: Extremely low-bit quantization for Transformers

|
tinyML Summit 2021 Keynote: Adaptive Neural Networks for Agile TinyML

tinyML Summit 2021 Keynote: Adaptive Neural Networks for Agile TinyML

|
tinyML Talks - Sek Chai: Adaptive AI for a Smarter Edge

tinyML Talks - Sek Chai: Adaptive AI for a Smarter Edge

|
tinyML Talks: on-device model fine-tuning for industrial anomaly detection applications

tinyML Talks: on-device model fine-tuning for industrial anomaly detection applications

|
Copyright. All rights reserved © 2025
Rosebank, Johannesburg, South Africa