https://github.com/squeezeailab/open_source_projects
Open Source Projects from Pallas Lab
https://github.com/squeezeailab/open_source_projects
Last synced: about 1 month ago
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Open Source Projects from Pallas Lab
- Host: GitHub
- URL: https://github.com/squeezeailab/open_source_projects
- Owner: SqueezeAILab
- License: mit
- Created: 2021-10-09T23:40:18.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2021-10-10T07:21:11.000Z (over 3 years ago)
- Last Synced: 2025-02-01T07:44:31.934Z (3 months ago)
- Size: 20.5 KB
- Stars: 20
- Watchers: 3
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Open Source Projects from PALLAS Lab
Below are links to different open source projects from [Prof. Keutzer](https://people.eecs.berkeley.edu/~keutzer)'s lab at UC Berkeley.
# Core Optimization Algorithms
* [AdaHessian: A Second-order Optimization Algorithm](https://github.com/amirgholami/adahessian)
* [HessianFlow: A Library for Hessian Based Algorithms in Machine Learning](https://github.com/amirgholami/HessianFlow)
* [PowerNorm: Rethinking Batch Normalization in Transformers](https://github.com/sIncerass/powernorm)
* [PyHessian: Neural Networks Through the Lens of the Hessian](https://github.com/amirgholami/PyHessian)
* [TRAttack: Trust Region Adversarial Attack](https://github.com/amirgholami/TRAttack)
# Neural Network Architecture Design
* [ANODE: Unconditionally Accurate Memory-efficient Gradients for Neural ODEs](https://github.com/amirgholami/anode)
* [DiracDeltaNet](https://github.com/Yang-YiFan/DiracDeltaNet)
* [Image2Point](https://github.com/chenfengxu714/image2point)
* [LiDAR](https://github.com/bernwang/LiDAR-annotator)
* [SqueezeNext: Hardware-aware Neural Network Design](https://github.com/amirgholami/SqueezeNext)
* [ShiftNet](https://github.com/alvinwan/shiftresnet-cifar)
* [SqueezeDet](https://github.com/BichenWuUCB/squeezeDet)
* [SqueezeSeg](https://github.com/BichenWuUCB/SqueezeSeg)
* [SqueezeSegV2](https://github.com/xuanyuzhou98/SqueezeSegV2)
* [SqueezeSegV3](https://github.com/chenfengxu714/SqueezeSegV3)
* [YOGO](https://github.com/chenfengxu714/YOGO)
# Efficient Inference and Compression
* [BitPack: A Practical Tool to Efficiently Save Ultra-Low Precision/Mixed-Precision Quantized Models](https://github.com/Zhen-Dong/BitPack)
* [CoDeNet: Efficient Deployment of Input-Adaptive Object Detection on Embedded FPGAs](https://github.com/Zhen-Dong/CoDeNet)
* [HAP: Hessian Aware Pruning and Neural Implant](https://github.com/yaozhewei/hap)
* [HAWQ: Hessian Aware Quantization](https://github.com/Zhen-Dong/HAWQ)
* [I-BERT: Integer Only BERT Quantization](https://github.com/kssteven418/I-BERT)
* [Q-ASR: Integer-only Zero-shot Quantization for Efficient Speech Recognition](https://github.com/kssteven418/Q-ASR)
* [ZeroQ: A Novel Zero Shot Quantization Framework](https://github.com/amirgholami/ZeroQ)
* [LTP: Learned Token Pruning](https://github.com/kssteven418/ltp)
# Domain Randomization and Domain Adaptation
* [MADAN](https://github.com/Luodian/MADAN)
* [PCS for Few-shot Unsupervised Domain Adaptation](https://github.com/zhengzangw/PCS-FUDA)