Rose-STL-Lab / AutoSTPP
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 6 months ago
Alternatives and similar repositories for AutoSTPP:
Users that are interested in AutoSTPP are comparing it to the libraries listed below
- Repository for the PopulAtion Parameter Averaging (PAPA) paper☆26Updated last year
- ☆11Updated 11 months ago
- ☆11Updated last year
- ☆11Updated 2 months ago
- Quantification of Uncertainty with Adversarial Models☆28Updated last year
- Code for "Accelerating Training with Neuron Interaction and Nowcasting Networks" [to appear at ICLR 2025]☆18Updated last month
- Generative cellular automaton-like learning environments for RL.☆19Updated 2 months ago
- Source code for the paper "Positional Attention: Out-of-Distribution Generalization and Expressivity for Neural Algorithmic Reasoning"☆14Updated 2 months ago
- A scalable implementation of diffusion and flow-matching with XGBoost models, applied to calorimeter data.☆18Updated 5 months ago
- ☆31Updated last year
- Pytorch (PyG) and Tensorflow (Keras/Spektral) implementation of Total Variation Graph Neural Network (TVGNN), as presented at ICML 2023.☆20Updated last month
- Official Implementation of NeurIPS'23 Paper "Cross-Episodic Curriculum for Transformer Agents"☆31Updated last year
- A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes☆25Updated 3 years ago
- Implementation of Spectral State Space Models☆16Updated last year
- A simple example of VAEs with KANs☆12Updated 11 months ago
- Supplementary code for the paper "Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces"☆42Updated last year
- JAX implementation of "Fine-Tuning Language Models with Just Forward Passes"☆19Updated last year
- Official code for paper: Conservative objective models are a special kind of contrastive divergence-based energy model☆14Updated last year
- Simple, extensible implementations of some meta-learning algorithms in Jax☆10Updated 4 years ago
- ☆17Updated 2 weeks ago
- ☆48Updated 3 months ago
- Official implementation of the paper "Interventions, Where and How? Experimental Design for Causal Models at Scale", NeurIPS 2022.☆20Updated 2 years ago
- PAC-Bayes generalization certificates for ICP☆21Updated last year
- Code for "Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations"☆23Updated 2 years ago
- ☆13Updated last year
- Neural Optimal Transport with Lagrangian Costs☆55Updated 9 months ago
- Official repository for the paper "Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules" (…☆22Updated 2 years ago
- Official repository for the paper "Goal-Conditioned Generators of Deep Policies"☆11Updated 2 years ago
- Neural Graphical models are neural network based graphical models that offer richer representation, faster inference & sampling☆28Updated last year
- Implementations of growing and pruning in neural networks☆22Updated last year