AishwaryaSivaraman / COMET
Counterexample-Guided Learning of Monotonic Networks
☆18Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for COMET
- A collection of commonly used datasets as benchmarks for density estimation in MaLe☆17Updated 5 years ago
- Generative Forests in Python☆33Updated last year
- Code for UAI'19: Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning☆36Updated 4 years ago
- A curated collection of papers on probabilistic circuits, computational graphs encoding tractable probability distributions.☆48Updated 9 months ago
- ☆50Updated last year
- Implementation of Bayesian Sum-Product Networks☆12Updated 4 years ago
- The Python PSDD Package☆16Updated 2 months ago
- Code source of Learning Binary Trees by Argmin Differentiation.☆12Updated last year
- A collection of commonly used datasets as benchmarks for density estimation☆24Updated 4 years ago
- ☆19Updated last year
- ☆15Updated 5 years ago
- Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains☆16Updated 6 years ago
- Library for learning and inference with Sum-product Networks utilizing TensorFlow 2.x and Keras☆47Updated 3 years ago
- Sum-Product Network learning routines in python☆26Updated 9 years ago
- Python library for working with graphons☆21Updated 7 years ago
- Probabilistic Circuits from the Juice library☆104Updated 5 months ago
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Updated 4 years ago
- Logistic Circuits☆35Updated 5 years ago
- PAC-Bayes with Backprop - Tighter risk certificates for neural networks☆24Updated 3 years ago
- Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)☆13Updated 4 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆76Updated 8 months ago
- PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020☆15Updated 3 years ago
- Fast Gradient Boosting Decision Trees with Bit-Level Data Structures☆16Updated 2 years ago
- Codebase for "Demystifying Black-box Models with Symbolic Metamodels", NeurIPS 2019.☆49Updated 5 years ago
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Updated last year
- Probabilistic Circuits in Julia☆9Updated 10 months ago
- A framework for composing Neural Processes in Julia☆76Updated 3 years ago
- ☆15Updated 2 years ago
- Gaussian Processes for Sequential Data☆18Updated 3 years ago
- Extension to multivariate unconstrained monotonic functions.☆11Updated 4 years ago