Recursive Cortical Network
George, Lavin, et al. Cortical Microcircuits from a Generative Vision Model. CCN 2018. /// paper
Hierarchical Temporal Memory
Hawkins, Lavin, et al. Biological and Machine Intelligence. 2016. /// book
Lavin (2019), Predictive Modeling Neurodegenerative Processes with a Domain-Specific Probabilistic Programming Language.
Haney & Lavin. Probabilistic Domain-Expert Hyperspherical Networks. CVPR Fine-grain Vision Workshop 2020.
Lavin. Integration of human-like covert-overt attention with probabilistic neural networks. Neuroscience to Artificially Intelligent Systems (NAISys) 2020.
Naud & Lavin (2020), Manifolds for Visual Anomaly Detection.
Lavin (2020), Probabilistic Programmed Causal Inference.
AI & ML articles
I contribute articles to Forbes on AI & ML, discussing important intersections with these technologies and society.
Machine learning systems can be massively useful, but also fail critically in unforeseen ways. We need systems engineering in synergy with experimentation and innovation.
Healthcare is ripe for the power of machine learning, but only with the scientific rigor of causal reasoning.
Black-box AI can be extremely powerful yet difficult to understand and trust. White-box AI is explainable and insightful, but sometimes at the cost of predictive power. How do we mend the gap?
Causal reasoning is a necessary ingredient to human-level artificial intelligence. We’re not there, yet.
On brains n bits, AI, and SW. For example,
- “Python for AI Research” on Talk Python to Me Podcast
- “How The Brain is Inspiring AI” at Forbes Under 30 summit