tml-epfl / why-weight-decay
Why Do We Need Weight Decay in Modern Deep Learning? [NeurIPS 2024]
☆60Updated 4 months ago
Alternatives and similar repositories for why-weight-decay:
Users that are interested in why-weight-decay are comparing it to the libraries listed below
- ☆51Updated 4 months ago
- ☆37Updated 10 months ago
- Sequence Modeling with Multiresolution Convolutional Memory (ICML 2023)☆122Updated last year
- Code for NeurIPS 2024 Spotlight: "Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations"☆70Updated 3 months ago
- HGRN2: Gated Linear RNNs with State Expansion☆52Updated 5 months ago
- ☆47Updated last year
- Revisiting Efficient Training Algorithms For Transformer-based Language Models (NeurIPS 2023)☆79Updated last year
- Code for the paper: Why Transformers Need Adam: A Hessian Perspective☆48Updated 9 months ago
- A fusion of a linear layer and a cross entropy loss, written for pytorch in triton.☆61Updated 6 months ago
- Latest Weight Averaging (NeurIPS HITY 2022)☆28Updated last year
- ☆51Updated 8 months ago
- The official repository for our paper "The Dual Form of Neural Networks Revisited: Connecting Test Time Predictions to Training Patterns …☆16Updated last year
- ☆30Updated 11 months ago
- Yet another random morning idea to be quickly tried and architecture shared if it works; to allow the transformer to pause for any amount…☆53Updated last year
- Implementation of Gated State Spaces, from the paper "Long Range Language Modeling via Gated State Spaces", in Pytorch☆97Updated last year
- ☆84Updated last year
- Triton Implementation of HyperAttention Algorithm☆46Updated last year
- ☆33Updated last year
- Official code for the paper "Attention as a Hypernetwork"☆23Updated 7 months ago
- Blog post☆16Updated 11 months ago
- Stick-breaking attention☆42Updated last month
- Official repository for the paper "Approximating Two-Layer Feedforward Networks for Efficient Transformers"☆36Updated last year
- Official repository of paper "RNNs Are Not Transformers (Yet): The Key Bottleneck on In-context Retrieval"☆25Updated 9 months ago
- ☆16Updated 7 months ago
- [ICLR 2023] "Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers" by Tianlong Chen*, Zhenyu Zhang*, Ajay Jaiswal…☆48Updated last year
- ☆28Updated 3 months ago
- [ICML 2024] SINGD: KFAC-like Structured Inverse-Free Natural Gradient Descent (http://arxiv.org/abs/2312.05705)☆21Updated 3 months ago
- Implementation of GateLoop Transformer in Pytorch and Jax☆87Updated 7 months ago
- Explorations into the recently proposed Taylor Series Linear Attention☆92Updated 5 months ago
- Official repository of "LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model Merging"☆24Updated 3 months ago