Rose-STL-Lab / AutoSTPPLinks
Automatic Integration for Neural Spatio-Temporal Point Process models (AI-STPP) is a new paradigm for exact, efficient, non-parametric inference of point process. It is capable of learning complicated underlying intensity functions, like a damped sine wave.
☆25Updated last year
Alternatives and similar repositories for AutoSTPP
Users that are interested in AutoSTPP are comparing it to the libraries listed below
Sorting:
- Deep Networks Grok All the Time and Here is Why☆38Updated last year
- Generative cellular automaton-like learning environments for RL.☆20Updated 11 months ago
- Quantification of Uncertainty with Adversarial Models☆29Updated 2 years ago
- code associated with paper "Sparse Bayesian Optimization"☆26Updated 2 years ago
- A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes☆25Updated 4 years ago
- Official repo for BWLer: Barycentric Weight Layer☆28Updated 3 months ago
- Repository for the PopulAtion Parameter Averaging (PAPA) paper☆29Updated last year
- ☆32Updated last year
- Implementation of Spectral State Space Models☆16Updated last year
- ☆35Updated last year
- Implementation of Gradient Agreement Filtering, from Chaubard et al. of Stanford, but for single machine microbatches, in Pytorch☆25Updated 11 months ago
- Pytorch implementation of SuperPolyak subgradient method.☆43Updated 3 years ago
- PAC-Bayes generalization certificates for ICP☆21Updated 2 years ago
- Experimental scripts for researching data adaptive learning rate scheduling.☆22Updated 2 years ago
- Jax like function transformation engine but micro, microjax☆34Updated last year
- A scalable implementation of diffusion and flow-matching with XGBoost models, applied to calorimeter data.☆18Updated last year
- Code related to different aspects of conformal learning☆17Updated 11 months ago
- Official Implementation of NeurIPS'23 Paper "Cross-Episodic Curriculum for Transformer Agents"☆31Updated 2 years ago
- Neural Optimal Transport with Lagrangian Costs☆61Updated 7 months ago
- Codes accompanying the paper "LaProp: a Better Way to Combine Momentum with Adaptive Gradient"☆29Updated 5 years ago
- Exploration into the Scaling Value Iteration Networks paper, from Schmidhuber's group☆37Updated last year
- A simple example of VAEs with KANs☆11Updated last year
- Unofficial but Efficient Implementation of "Mamba: Linear-Time Sequence Modeling with Selective State Spaces" in JAX☆92Updated last year
- JAX implementation of "Fine-Tuning Language Models with Just Forward Passes"☆19Updated 2 years ago
- Official Implementation of the ICML 2023 paper: "Neural Wave Machines: Learning Spatiotemporally Structured Representations with Locally …☆77Updated 2 years ago
- Portfolio REgret for Confidence SEquences☆20Updated last week
- Code for minimum-entropy coupling.☆32Updated last week
- Implementation and explorations into Blackbox Gradient Sensing (BGS), an evolutionary strategies approach proposed in a Google Deepmind p…☆20Updated 5 months ago
- Repo for the paper "Landscape Surrogate Learning Decision Losses for Mathematical Optimization Under Partial Information"☆38Updated 2 years ago
- Meta-learning inductive biases in the form of useful conserved quantities.☆39Updated 3 years ago