- Andrej Risteski (Generative Model & MCMC)
- almost stochastic
- arg min
- Contour Samplers
- Greg
- inFERENCe
- Inverse Probability - Neil Lawrence
- I’m a bandit
- Djalil Chafaï
- Eric Jiang, Flow in JAX
- Hopfield Networks is All You Need
- Lil'Log
- LLM
- Ilya V. Schurov
- Machine Learning Research
- Piecewise Deterministic Monte Carlo
- Probably Approximately Wrong
- Sam Power (MCMC)
- Sander Dieleman (Diffusion Models)
- Sebastian's Slow Blog
- The Information Structuralist
- Transformer Circuits Thread
- Tuan Anh Le
- VAIBHAV PATEL
- Yuling Yao's Blog
- The Annotated S4
- Simplifying S4
- KL Divergence
- 苏剑林 科学空间
- 紫气东来 LLM
-
Contour Sampler is the first algorithm that achieves the real free explorations and exploitations in MNIST dataset [Demo]; most other samplers cannot escape the high-energy barriers and only optimize well locally.
-
Non-reversible Parallel Tempering: cosine learning rates work well empirically because it mimics non-reversible parallel tempering
-
NLP in Finance leverages sentiment analysis to predict stock price movement based on News headlines
-
DeepLight ever won SOTA for CTR prediction in Ad Serving
![[Demo]](https://github.com/WayneDW/Interacting-Contour-Stochastic-Gradient-Langevin-Dynamics/blob/main/figures/ICSGLD_losses_path.gif){kind=link}