My main R&D initiatives and papers are listed below. Please see my Google Scholar and arXiv profiles for all my research papers.

Key: πŸ‘Ύ AI/ML, 🧠 neuro, πŸ€– robotics, 🌎 Earth+space sciences, πŸ›° systems, πŸ’Š healthcare

Main initiatives (with papers)

Recursive Cortical Network πŸ‘ΎπŸ§ πŸ€–

  • George, Lavin, et al. A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs. Science 2017. /// paper, blog, code

  • George, Lavin, et al. Cortical Microcircuits from a Generative Vision Model. CCN 2018. /// paper

Hierarchical Temporal Memory πŸ‘ΎπŸ§ πŸ€–

  • Ahmad, Lavin, et al. Unsupervised real-time anomaly detection for streaming data. Neurocomputing 2017. /// paper, code

  • Hawkins, Lavin, et al. Biological and Machine Intelligence. 2016. /// book

Systems AI πŸ›°πŸ‘Ύ

  • Lavin et al (2021), Technology Readiness Levels for Machine Learning Systems. /// preprint

  • Lavin. Towards Systems AI & Decisions Intelligence. 2021 Spring AAAI Symposium. /// preprint

  • Lavin & Renard. Technology Readiness Levels for Artificial Intelligence & Machine Learning. ICML 2020 Workshop on Challenges in Deploying ML Systems. /// paper

Other recent papers

  • Lavin. Neuro-symbolic Neurodegenerative Disease Modeling as Probabilistic Programmed Deep Kernels. 2021 International Workshop on Health Intelligence /// paper /// πŸ‘ΎπŸ’Š
  • Lavin (2021), Probabilistic Programmed Causal Inference. /// πŸ‘Ύ
  • Naud & Lavin (2020), Manifolds for Unsupervised Visual Anomaly Detection. /// paper

  • Haney & Lavin. Fine-Grain Few-Shot Vision via Domain Knowledge as Hyperspherical Priors. CVPR Fine-grain Vision Workshop 2020. /// paper, video

  • Lutjens, Lavin, et al (2020). Physics-informed GANs for Coastal Flood Visualization. /// paper, demo /// πŸŒŽπŸ‘Ύ

  • Lippoldt & Lavin. Attention-Sampling Graph Convolutional Networks. 2020 BayLearn Symposium. /// πŸ‘ΎπŸ’Š

  • Lavin (2020), Accelerating Gaussian Processes and Deep Kernel Networks on GPUs. /// video /// πŸ‘Ύ

  • Lavin (2019), Predictive Modeling Neurodegenerative Processes with a Domain-Specific Probabilistic Programming Language. /// πŸ‘ΎπŸ’Š

  • Lavin. Integration of human-like covert-overt attention with probabilistic neural networks. Neuroscience to Artificially Intelligent Systems (NAISys) 2020. /// abs /// πŸ§ πŸ‘Ύ