Calibration of high-precision flexure parallel robots

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Integer linear programming (ILP) is an elegant approach to solve linear optimization problems, naturally described using integer decision variables. Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relev ...

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, ...

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Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

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In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

The Birman-Williams theorem gives a connection between the collection of unstable periodic orbits (UPOs) contained within a chaotic attractor and the topology of that attractor, for three-dimensional systems. In certain cases, the fractal dimension of a ch ...

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We present a finite elements-neural network approach for the numerical approximation of parametric partial differential equations. The algorithm generates training data from finite element simulations, and uses a data -driven (supervised) feedforward neura ...

Calibration of high-precision flexure parallel robots

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Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Enhancing skin lesion classification: a CNN approach with human baseline comparison

Generalization of Scaled Deep ResNets in the Mean-Field Regime

A Reconfigurable High-Dynamic Range ∆Σ Front-End with Event-Based Decimation for Bandwidth-Efficient Implantable Neural Interfaces

Safe Deep Neural Networks

Retrieval of Surface Solar Radiation through Implicit Albedo Recovery from Temporal Context

Robust machine learning for neuroscientific inference

Neural Garment Modeling

Robot Learning using Tensor Networks

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

MetaCap: Meta-learning Priors from Multi-view Imagery for Sparse-View Human Performance Capture and Rendering

Optimizing Dynamic Aperture Studies with Active Learning

MammAlps: A multi-view video behavior monitoring dataset of wild mammals in the Swiss Alps

Gibbs sampling the posterior of neural networks

The topology of a chaotic attractor in the Kuramoto-Sivashinsky equation

Machine Learning for Modeling Stock Returns

Adapting Fine-Grained Cross-View Localization to Areas Without Fine Ground Truth

Error assessment of an adaptive finite elements-neural networks method for an elliptic parametric PDE