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.
☆26Updated 11 months ago
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☆37Updated last year
- Generative cellular automaton-like learning environments for RL.☆19Updated 7 months ago
- Quantification of Uncertainty with Adversarial Models☆29Updated 2 years ago
- A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes☆25Updated 3 years ago
- ☆34Updated last year
- Official Implementation of NeurIPS'23 Paper "Cross-Episodic Curriculum for Transformer Agents"☆31Updated last year
- Repository for the PopulAtion Parameter Averaging (PAPA) paper☆27Updated last year
- ☆17Updated 5 months ago
- ☆32Updated last year
- Implementation and explorations into Blackbox Gradient Sensing (BGS), an evolutionary strategies approach proposed in a Google Deepmind p…☆18Updated last month
- Official Implementation of the ICML 2023 paper: "Neural Wave Machines: Learning Spatiotemporally Structured Representations with Locally …☆73Updated 2 years ago
- Jax like function transformation engine but micro, microjax☆33Updated 10 months ago
- Fast singularity detection with kernel☆37Updated last year
- A simple example of VAEs with KANs☆12Updated last year
- Neural Optimal Transport with Lagrangian Costs☆57Updated 3 months ago
- Implementation of Gradient Agreement Filtering, from Chaubard et al. of Stanford, but for single machine microbatches, in Pytorch☆25Updated 7 months ago
- Unofficial but Efficient Implementation of "Mamba: Linear-Time Sequence Modeling with Selective State Spaces" in JAX☆88Updated last year
- GBRL-based Actor-Critic algorithms implemented in stable-baselines3☆38Updated last month
- Multi-Agent Verification: Scaling Test-Time Compute with Multiple Verifiers☆20Updated 6 months ago
- Repo for the paper "Landscape Surrogate Learning Decision Losses for Mathematical Optimization Under Partial Information"☆36Updated 2 years ago
- ☆31Updated last year
- A scalable implementation of diffusion and flow-matching with XGBoost models, applied to calorimeter data.☆18Updated 10 months ago
- Official implementation of E(n)-equivariant Graph Neural Cellular Automata☆31Updated last year
- Pytorch (PyG) and Tensorflow (Keras/Spektral) implementation of Total Variation Graph Neural Network (TVGNN), as presented at ICML 2023.☆20Updated 6 months ago
- ☆40Updated last year
- Gradient Boosting Reinforcement Learning (GBRL)☆118Updated last month
- Unofficial implementation of Conformal Language Modeling by Quach et al☆29Updated 2 years ago
- JAX implementation of "Fine-Tuning Language Models with Just Forward Passes"☆19Updated 2 years ago
- Source code for the paper "Positional Attention: Expressivity and Learnability of Algorithmic Computation"☆14Updated 3 months ago
- Repo to reproduce the First-Explore paper results☆38Updated 8 months ago