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.
☆24Updated 8 months ago
Alternatives and similar repositories for AutoSTPP
Users that are interested in AutoSTPP are comparing it to the libraries listed below
Sorting:
- Generative cellular automaton-like learning environments for RL.☆19Updated 4 months ago
- ☆11Updated 2 years ago
- Code for "Accelerating Training with Neuron Interaction and Nowcasting Networks" [to appear at ICLR 2025]☆19Updated last month
- Pytorch (PyG) and Tensorflow (Keras/Spektral) implementation of Total Variation Graph Neural Network (TVGNN), as presented at ICML 2023.☆20Updated 3 months ago
- Repository for the PopulAtion Parameter Averaging (PAPA) paper☆26Updated last year
- ☆11Updated last year
- Official repository for the paper "Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules" (…☆22Updated 2 weeks ago
- Official Implementation of NeurIPS'23 Paper "Cross-Episodic Curriculum for Transformer Agents"☆31Updated last year
- ☆11Updated 4 months ago
- ☆17Updated 2 months ago
- Official implementation of E(n)-equivariant Graph Neural Cellular Automata☆28Updated last year
- A scalable implementation of diffusion and flow-matching with XGBoost models, applied to calorimeter data.☆18Updated 7 months ago
- A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes☆25Updated 3 years ago
- JAX implementation of "Fine-Tuning Language Models with Just Forward Passes"☆19Updated 2 years ago
- ☆32Updated last year
- Deep Networks Grok All the Time and Here is Why☆37Updated last year
- "How to Trust Your Diffusion Models: A Convex Optimization Approach to Conformal Risk Control"☆17Updated 3 weeks ago
- PAC-Bayes generalization certificates for ICP☆21Updated last year
- Code for "Continuous-Time Meta-Learning with Forward Mode Differentiation" (ICLR 2022)☆25Updated 3 years ago
- ☆13Updated 2 years ago
- A simple example of VAEs with KANs☆12Updated last year
- Implementation of Spectral State Space Models☆16Updated last year
- Source code for the paper "Positional Attention: Expressivity and Learnability of Algorithmic Computation"☆14Updated last month
- ☆10Updated 3 years ago
- Fast singularity detection with kernel☆33Updated last year
- Quantification of Uncertainty with Adversarial Models☆29Updated last year
- ☆16Updated last year
- Official code for paper: Conservative objective models are a special kind of contrastive divergence-based energy model☆14Updated last year
- Implementation of Gradient Agreement Filtering, from Chaubard et al. of Stanford, but for single machine microbatches, in Pytorch☆25Updated 5 months ago
- ☆31Updated last year