WheaCha: A Method for Explaining the Predictions of Models of Code

Kavli Affiliate: Ke Wang | First 5 Authors: Yu Wang, Ke Wang, Linzhang Wang, , | Summary: Attribution methods have emerged as a popular approach to interpreting model predictions based on the relevance of input features. Although the feature importance ranking can provide insights of how models arrive at a prediction from a raw input, […]


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How does the Polar Dust affect the Correlation between Dust Covering Factor and Eddington Ratio in Type 1 Quasars Selected from the Sloan Digital Sky Survey Data Release 16?

Kavli Affiliate: Claudio Ricci | First 5 Authors: Yoshiki Toba, Yoshihiro Ueda, Poshak Gandhi, Claudio Ricci, Denis Burgarella | Summary: We revisit the dependence of covering factor (CF) of dust torus on physical properties of active galactic nuclei (AGNs) by taking into account an AGN polar dust emission. The CF is converted from a ratio […]


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Realization of a multi-node quantum network of remote solid-state qubits

Kavli Affiliate: Ronald Hanson | First 5 Authors: Matteo Pompili, Sophie L. N. Hermans, Simon Baier, Hans K. C. Beukers, Peter C. Humphreys | Summary: The distribution of entangled states across the nodes of a future quantum internet will unlock fundamentally new technologies. Here we report on the experimental realization of a three-node entanglement-based quantum […]


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BAT AGN Spectroscopic Survey-XXIII. A New Mid-Infrared Diagnostic for Absorption in Active Galactic Nuclei

Kavli Affiliate: Claudio Ricci | First 5 Authors: Ryan W. Pfeifle, Claudio Ricci, Peter G. Boorman, Marko Stalevski, Daniel Asmus | Summary: In this study, we use the SWIFT/BAT AGN sample, which has received extensive multiwavelength follow-up analysis as a result of the BAT AGN Spectroscopic Survey (BASS), to develop a diagnostic for nuclear obscuration […]


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Introduction to Machine Learning for the Sciences

Kavli Affiliate: Eliska Greplova | First 5 Authors: Titus Neupert, Mark H Fischer, Eliska Greplova, Kenny Choo, Michael Denner | Summary: This is an introductory machine learning course specifically developed with STEM students in mind. We discuss supervised, unsupervised, and reinforcement learning. The notes start with an exposition of machine learning methods without neural networks, […]


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Breaking the degeneracy between polarization efficiency and cosmological parameters in CMB experiments

Kavli Affiliate: W. L. Kimmy Wu | First 5 Authors: Silvia Galli, W. L. Kimmy Wu, Karim Benabed, François Bouchet, Thomas M. Crawford | Summary: Accurate cosmological parameter estimates using polarization data of the cosmic microwave background (CMB) put stringent requirements on map calibration, as highlighted in the recent results from the Planck satellite. In […]


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Opportunities for DOE National Laboratory-led QuantISED Experiments

Kavli Affiliate: Peter Graham | First 5 Authors: Pete Barry, Karl Berggren, A. Baha Balantekin, John Bollinger, Ray Bunker | Summary: A subset of QuantISED Sensor PIs met virtually on May 26, 2020 to discuss a response to a charge by the DOE Office of High Energy Physics. In this document, we summarize the QuantISED […]


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CharacterGAN: Few-Shot Keypoint Character Animation and Reposing

Kavli Affiliate: Matthew Fisher | First 5 Authors: Tobias Hinz, Matthew Fisher, Oliver Wang, Eli Shechtman, Stefan Wermter | Summary: We introduce CharacterGAN, a generative model that can be trained on only a few samples (8 – 15) of a given character. Our model generates novel poses based on keypoint locations, which can be modified […]


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Adiabatic waveforms for extreme mass-ratio inspirals via multivoice decomposition in time and frequency

Kavli Affiliate: Scott A. Hughes | First 5 Authors: Scott A. Hughes, Niels Warburton, Gaurav Khanna, Alvin J. K. Chua, Michael L. Katz | Summary: We compute adiabatic waveforms for extreme mass-ratio inspirals (EMRIs) by "stitching" together a long inspiral waveform from a sequence of waveform snapshots, each of which corresponds to a particular geodesic […]


Continue.. Adiabatic waveforms for extreme mass-ratio inspirals via multivoice decomposition in time and frequency

Adiabatic waveforms for extreme mass-ratio inspirals via multivoice decomposition in time and frequency

Kavli Affiliate: Scott A. Hughes | First 5 Authors: Scott A. Hughes, Niels Warburton, Gaurav Khanna, Alvin J. K. Chua, Michael L. Katz | Summary: We compute adiabatic waveforms for extreme mass-ratio inspirals (EMRIs) by "stitching" together a long inspiral waveform from a sequence of waveform snapshots, each of which corresponds to a particular geodesic […]


Continue.. Adiabatic waveforms for extreme mass-ratio inspirals via multivoice decomposition in time and frequency