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 17 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
Can LLMs Predict Their Own Failures? Self-Awareness via Internal Circuits
internal orm efficient circuits attention reasoning error-detection hallucination self-awareness latent-representations gnosis-safe llm large-language-model reward-model hallucination-detection
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Jan 8, 2026 - 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
Variational Interpretable Concept Embeddings
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Dec 12, 2023 - 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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May 9, 2025 - 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
Investigates causal visual reasoning in transformers by integrating discrete latent image tokens (VQGAN) as internal representations for spatial reasoning and decision making.
deep-learning transformers causal-inference visual-reasoning latent-representations vqgan mechanistic-interpretability multimodal-ai
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Mar 16, 2026 - Python
A multi-criterion diagnostic framework for detecting latent continuation-interest signatures in autonomous agents using density-matrix entanglement entropy.
benchmarking reproducible-research representation-learning trajectory-analysis mutual-information autonomous-agents ai-safety interpretability latent-representations behavioral-analysis objective-detection quantum-inspired quantum-boltzmann-machine persistence-detection entanglement-entropy self-preservation agent-evaluation alignment-research continuation-interest artificial-agency
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Apr 1, 2026 - Python
Hyperprobe is the Python implementation of the framework proposed in the paper "Hyperdimensional Probe: Decoding LLM Representations via Vector Symbolic Architectures".
language-models probes interpretability latent-representations vector-symbolic-architectures llms information-decoding residual-stream
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Oct 3, 2025 - 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
Patch-token geometry benchmarks for released vision encoders (DINOv2, I-JEPA, V-JEPA 2, and EUPE)
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May 6, 2026 - Python
Stable Customer Segmentation is an end-to-end ML pipeline that learns latent customer representations using autoencoders before applying clustering, enabling more stable and interpretable customer segmentation compared to traditional feature-space clustering approaches.
machine-learning deep-learning clustering autoencoder representation-learning feature-engineering unsupervised-learning customer-segmentation fmcg latent-representations ml-pipeline retail-analytics
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Mar 15, 2026 - 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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