There are 3 repositories under efficient-model topic.
[ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding
[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment
[ICLR 2019] ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware
[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices
[CVPR 2019, Oral] HAQ: Hardware-Aware Automated Quantization with Mixed Precision
[ACL'20] HAT: Hardware-Aware Transformers for Efficient Natural Language Processing
[NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
[CVPR'20] ZeroQ: A Novel Zero Shot Quantization Framework
[ICML'21 Oral] I-BERT: Integer-only BERT Quantization
[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices
Efficient 3D Backbone Network for Temporal Modeling
[KDD'22] Learned Token Pruning for Transformers
Any-Precision Deep Neural Networks (AAAI 2021)
[JMLR'20] NeurIPS 2019 MicroNet Challenge Efficient Language Modeling, Champion
[MICCAI 2021] BiX-NAS: Searching Efficient Bi-directional Architecture for Medical Image Segmentation
Concise, Modular, Human-friendly PyTorch implementation of EfficientNet with Pre-trained Weights.
[ICASSP'22] Integer-only Zero-shot Quantization for Efficient Speech Recognition
NeurIPSCD2019, MicroNet Challenge hosted by Google, Deepmind Researcher, "Efficient Model for Image Classification With Regularization Tricks".
GraphSnapShot: Caching Local Structure for Fast Graph Learning
Concise, Modular, Human-friendly PyTorch implementation of MixNet with Pre-trained Weights.
[Thesis'24] Efficient Class Incremental Learning for Object Detection
Extremely light-weight MixNet with Top-1 75.7% and 2.5M params
Implementation of efficient backbones for computer vision task.
Exploring Variational Deep Q Networks. A study undertaken for the University of Cambridge's R244 Computer Science Masters Course. Inspired by https://arxiv.org/abs/1711.11225/.
Melanoma Classification using Semi-supervised learning
Explore image transformations with DeepDream Algorithm and Neural Style Transfer in creative image processing.
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