Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learning
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Mar 24, 2023 - Python
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latent-representations
Here are 11 public repositories matching this topic...
Implementation of "Disentangled Representation Learning for Non-Parallel Text Style Transfer(ACL 2019)" in Pytorch
acl pytorch style-transfer natural-language-generation adversarial-learning variational-autoencoder disentanglement disentangled-representations text-style-transfer latent-representations
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Oct 25, 2024 - Python
This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help of a corpus of examples. For more details, please read our NeurIPS 2021 paper: 'Explaining Latent Representations with a Corpus of Examples'.
machine-learning artificial-intelligence neural-networks method interpretability feature-importance explainable-ai latent-space latent-representations neurips example-based-explanations neurips-2021
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Jan 31, 2023 - Python
Code for our paper -- Hyperprior Induced Unsupervised Disentanglement of Latent Representations (AAAI 2019)
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Jan 16, 2019 - Python
Tripod is a tool/ML model for computing latent representations for large sequences
machine-learning machine-learning-algorithms python3 seq2seq unsupervised-learning distributed-representations latent-representations
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Apr 8, 2024 - Python
Variational Interpretable Concept Embeddings
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Dec 12, 2023 - Python
Code associated with the paper "Prior Image-Constrained Reconstruction using Style-Based Generative Models" accepted to ICML 2021.
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Jun 14, 2021 - Python
Latent-Explorer is the Python implementation of the framework proposed in the paper "Unveiling LLMs: The Evolution of Latent Representations in a Dynamic Knowledge Graph".
knowledge graphs knowledge-graph probing latent-representations factuality llms llms-reasoning propositional-probes claim-verification
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Oct 21, 2024 - Python
Investigate mapping of articulations from the image space to the latent space using neural networks.
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Nov 3, 2022 - Python
Working towards deliverable 5.3
journal paper biomarker-discovery latent-semantic-analysis stacked-denoising-autoencoders latent-representations
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Jul 4, 2021 - Python
This algorithm exploits the relationships between variables to improve the reconstruction performance of the variational autoencoder (VAE). A correlation score was used as the metric to group the features via a distance-based clustering method. The resulting clusters served as inputs for the Attention-Based VAE.
clustering attention-mechanism time-series-analysis variational-autoencoder dynamic-thresholding latent-representations
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Sep 14, 2024 - Python
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