[ICML 2021] "Double-Win Quant: Aggressively Winning Robustness of Quantized DeepNeural Networks via Random Precision Training and Inference" by Yonggan Fu, Qixuan Yu, Meng Li, Vikas Chandra, Yingyan Lin
☆16Feb 13, 2022Updated 4 years ago
Alternatives and similar repositories for Double-Win-Quant
Users that are interested in Double-Win-Quant are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- The official code for [ECCV2020] "HALO: Hardware-aware Learning to Optimize"☆10Mar 22, 2023Updated 3 years ago
- [NeurIPS 2021] "Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks" by Yon…☆13Feb 13, 2022Updated 4 years ago
- Code needed to reproduce results from my ICLR 2019 paper on fixed-point quantization of the backprop algorithm.☆10Jan 24, 2019Updated 7 years ago
- [NeurIPS 2020] ShiftAddNet: A Hardware-Inspired Deep Network☆74Nov 16, 2020Updated 5 years ago
- Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples [NeurIPS 2021]☆34Dec 12, 2021Updated 4 years ago
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- [ICML 2025] LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models☆18Nov 4, 2025Updated 6 months ago
- pytorch implementation of Parametric Noise Injection for adversarial defense☆46Oct 23, 2019Updated 6 years ago
- Revisit Kernel Pruning with Lottery Regulated Grouped Convolutions. ICLR 2022☆11Nov 24, 2022Updated 3 years ago
- [NeurIPS2021] Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks☆33Jul 5, 2024Updated last year
- [CVPR2025] Divide and Conquer: Heterogeneous Noise Integration for Diffusion-based Adversarial Purification☆16Nov 9, 2025Updated 5 months ago
- Neural Network Quantization With Fractional Bit-widths☆11Feb 19, 2021Updated 5 years ago
- Official Implementation for CVPR 2025 paper Instant Adversarial Purification with Adversarial Consistency Distillation.☆15Dec 19, 2025Updated 4 months ago
- codes for ICML2021 paper iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients☆10May 27, 2021Updated 4 years ago
- [NeurIPS 2023] ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer☆30Dec 6, 2023Updated 2 years ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- gradient norm penalty☆41Jun 17, 2024Updated last year
- BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization (ICLR 2021)☆42Jan 12, 2021Updated 5 years ago
- helper functions for processing and integrating visual language information with Qwen-VL Series Model☆18Aug 30, 2024Updated last year
- [ICLR 2022 Oral] F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization☆93May 5, 2022Updated 3 years ago
- PyTorch implementation of Towards Efficient Training for Neural Network Quantization☆16Jan 16, 2020Updated 6 years ago
- Big Data and Machine Intelligence, Spring 2021.☆12Jul 2, 2021Updated 4 years ago
- Scripts to prepare OXFORD VGG Face dataset☆12Mar 29, 2016Updated 10 years ago
- ☆49Jan 21, 2022Updated 4 years ago
- [ICLR 2025] Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching☆19Apr 21, 2025Updated last year
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- The code of the ICLR 2024 paper: Adversarial Training on Purification (AToP): Advancing Both Robustness and Generalization☆10Nov 21, 2024Updated last year
- An open-sourced PyTorch library for developing energy efficient multiplication-less models and applications.☆14Feb 3, 2025Updated last year
- ☆29Nov 5, 2021Updated 4 years ago
- [NeurIPS 2020] "FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training" by Yonggan Fu, Ha…☆10Feb 13, 2022Updated 4 years ago
- Official Code For Dual Grained Quantization: Efficient Fine-Grained Quantization for LLM☆14Dec 27, 2023Updated 2 years ago
- BitSplit Post-trining Quantization☆49Dec 20, 2021Updated 4 years ago
- Deep Random Projector: Accelerated Deep Image Prior☆18Jun 9, 2023Updated 2 years ago
- Pytorch implementation of Adversarially Robust Distillation (ARD)☆59May 24, 2019Updated 6 years ago
- An Tensorflow.keras implementation of Same, Same But Different - Recovering Neural Network Quantization Error Through Weight Factorizatio…☆10Dec 18, 2019Updated 6 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- Application of REINFORCE algorithm to downlink NOMA system☆13Jan 28, 2026Updated 3 months ago
- [ICML 2022] ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks☆15May 18, 2022Updated 3 years ago
- ☆12Mar 15, 2019Updated 7 years ago
- Implementation for What it Thinks is Important is Important: Robustness Transfers through Input Gradients (CVPR 2020 Oral)☆16Mar 24, 2023Updated 3 years ago
- [NeurIPS 2022] "Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Spee…☆17Sep 19, 2023Updated 2 years ago
- An FL algorithm inspired by FedGMA☆11Oct 21, 2023Updated 2 years ago
- Implementation of NM sparsity recipe presented in the paper "Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers".☆11Feb 5, 2024Updated 2 years ago