Search Results for author: Alexander Lavin

Found 19 papers, 6 papers with code

Multi-scale Digital Twin: Developing a fast and physics-informed surrogate model for groundwater contamination with uncertain climate models

no code implementations20 Nov 2022 Lijing Wang, Takuya Kurihana, Aurelien Meray, Ilijana Mastilovic, Satyarth Praveen, Zexuan Xu, Milad Memarzadeh, Alexander Lavin, Haruko Wainwright

To quickly assess the spatiotemporal variations of groundwater contamination under uncertain climate disturbances, we developed a physics-informed machine learning surrogate model using U-Net enhanced Fourier Neural Operator (U-FNO) to solve Partial Differential Equations (PDEs) of groundwater flow and transport simulations at the site scale. We develop a combined loss function that includes both data-driven factors and physical boundary constraints at multiple spatiotemporal scales.

Management Online Clustering +1

Physical Computing for Materials Acceleration Platforms

no code implementations17 Aug 2022 Erik Peterson, Alexander Lavin

A ''technology lottery'' describes a research idea or technology succeeding over others because it is suited to the available software and hardware, not necessarily because it is superior to alternative directions--examples abound, from the synergies of deep learning and GPUs to the disconnect of urban design and autonomous vehicles.

Autonomous Vehicles

The Unreasonable Effectiveness of Deep Evidential Regression

1 code implementation20 May 2022 Nis Meinert, Jakob Gawlikowski, Alexander Lavin

There is a significant need for principled uncertainty reasoning in machine learning systems as they are increasingly deployed in safety-critical domains.


Multivariate Deep Evidential Regression

1 code implementation13 Apr 2021 Nis Meinert, Alexander Lavin

We discuss three issues with a proposed solution to extract aleatoric and epistemic uncertainties from regression-based neural networks.


Learnings from Frontier Development Lab and SpaceML -- AI Accelerators for NASA and ESA

no code implementations9 Nov 2020 Siddha Ganju, Anirudh Koul, Alexander Lavin, Josh Veitch-Michaelis, Meher Kasam, James Parr

Research with AI and ML technologies lives in a variety of settings with often asynchronous goals and timelines: academic labs and government organizations pursue open-ended research focusing on discoveries with long-term value, while research in industry is driven by commercial pursuits and hence focuses on short-term timelines and return on investment.

Neuro-symbolic Neurodegenerative Disease Modeling as Probabilistic Programmed Deep Kernels

no code implementations16 Sep 2020 Alexander Lavin

We present a probabilistic programmed deep kernel learning approach to personalized, predictive modeling of neurodegenerative diseases.

BIG-bench Machine Learning Disease Prediction +2

Technology Readiness Levels for AI & ML

no code implementations21 Jun 2020 Alexander Lavin, Gregory Renard

Drawing on experience in both spacecraft engineering and AI/ML (from research through product), we propose a proven systems engineering approach for machine learning development and deployment.

BIG-bench Machine Learning

Manifolds for Unsupervised Visual Anomaly Detection

1 code implementation19 Jun 2020 Louise Naud, Alexander Lavin

Through theoretical and empirical explorations of manifold shapes, we develop a novel hyperspherical Variational Auto-Encoder (VAE) via stereographic projections with a gyroplane layer - a complete equivalent to the Poincar\'e VAE.

Anomaly Detection whole slide images

Fine-Grain Few-Shot Vision via Domain Knowledge as Hyperspherical Priors

no code implementations23 May 2020 Bijan Haney, Alexander Lavin

Prototypical networks have been shown to perform well at few-shot learning tasks in computer vision.

Classification Few-Shot Learning +1

Doubly Bayesian Optimization

no code implementations11 Dec 2018 Alexander Lavin

Probabilistic programming systems enable users to encode model structure and naturally reason about uncertainties, which can be leveraged towards improved Bayesian optimization (BO) methods.

Bayesian Optimization Probabilistic Programming

Cortical Microcircuits from a Generative Vision Model

no code implementations3 Aug 2018 Dileep George, Alexander Lavin, J. Swaroop Guntupalli, David Mely, Nick Hay, Miguel Lazaro-Gredilla

Understanding the information processing roles of cortical circuits is an outstanding problem in neuroscience and artificial intelligence.

Bayesian Inference

Clustering Time-Series Energy Data from Smart Meters

no code implementations24 Mar 2016 Alexander Lavin, Diego Klabjan

Investigations have been performed into using clustering methods in data mining time-series data from smart meters.

Time Series Analysis

A Pareto Optimal D* Search Algorithm for Multiobjective Path Planning

no code implementations3 Nov 2015 Alexander Lavin

The global path plan can be calculated with a variety of informed search algorithms, most notably the A* search method, guaranteed to deliver a complete and optimal solution that minimizes the path cost.

Multiobjective Optimization

Evaluating Real-time Anomaly Detection Algorithms - the Numenta Anomaly Benchmark

3 code implementations12 Oct 2015 Alexander Lavin, Subutai Ahmad

Here we propose the Numenta Anomaly Benchmark (NAB), which attempts to provide a controlled and repeatable environment of open-source tools to test and measure anomaly detection algorithms on streaming data.

Anomaly Detection Time Series Analysis

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