368 citations · 1k across the 15 of their papers we have counts for
16 papers
What Hawking Radiation Looks Like as You Fall into a Black Hole
Christopher J. Shallue, Sean M. Carroll
We study the measurements of a freely falling Unruh-DeWitt particle detector near the horizon of a semiclassical Schwarzschild black hole. Our results show that the detector's resp…
Warm Hawking Relics From Primordial Black Hole Domination
Christopher J. Shallue, Julian B. Muñoz, Gordan Z. Krnjaic
We study the cosmological impact of warm, dark-sector relic particles produced as Hawking radiation in a primordial-black-hole-dominated universe before big bang nucleosynthesis. I…
Characterization of K2-167 b and CALM, a new stellar activity mitigation method
Zoë L. de Beurs, Andrew Vanderburg, Erica Thygesen +13
We report precise radial velocity (RV) observations of HD 212657 (= K2-167), a star shown by K2 to host a transiting sub-Neptune-sized planet in a 10 day orbit. Using Transiting Ex…
Reconstructing Cosmological Initial Conditions from Late-Time Structure with Convolutional Neural Networks
Christopher J. Shallue, Daniel J. Eisenstein
We present a method to reconstruct the initial linear-regime matter density field from the late-time non-linearly evolved density field in which we channel the output of standard f…
The EXPRES Stellar Signals Project II. State of the Field in Disentangling Photospheric Velocities
Lily L. Zhao, Debra A. Fischer, Eric B. Ford +40
Measured spectral shifts due to intrinsic stellar variability (e.g., pulsations, granulation) and activity (e.g., spots, plages) are the largest source of error for extreme precisi…
A Large Batch Optimizer Reality Check: Traditional, Generic Optimizers Suffice Across Batch Sizes
Zachary Nado, Justin M. Gilmer, Christopher J. Shallue +2
Recently the LARS and LAMB optimizers have been proposed for training neural networks faster using large batch sizes. LARS and LAMB add layer-wise normalization to the update rules…
Identifying Exoplanets with Deep Learning. IV. Removing Stellar Activity Signals from Radial Velocity Measurements Using Neural Networks
Zoe L. de Beurs, Andrew Vanderburg, Christopher J. Shallue +24
Exoplanet detection with precise radial velocity (RV) observations is currently limited by spurious RV signals introduced by stellar activity. We show that machine learning techniq…
On Empirical Comparisons of Optimizers for Deep Learning
Dami Choi, Christopher J. Shallue, Zachary Nado +3
Selecting an optimizer is a central step in the contemporary deep learning pipeline. In this paper, we demonstrate the sensitivity of optimizer comparisons to the hyperparameter tu…
Faster Neural Network Training with Data Echoing
Dami Choi, Alexandre Passos, Christopher J. Shallue +1
In the twilight of Moore's law, GPUs and other specialized hardware accelerators have dramatically sped up neural network training. However, earlier stages of the training pipeline…
Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model
Guodong Zhang, Lala Li, Zachary Nado +5
Increasing the batch size is a popular way to speed up neural network training, but beyond some critical batch size, larger batch sizes yield diminishing returns. In this work, we…
Identifying Exoplanets with Deep Learning III: Automated Triage and Vetting of TESS Candidates
Liang Yu, Andrew Vanderburg, Chelsea Huang +14
NASA's Transiting Exoplanet Survey Satellite (TESS) presents us with an unprecedented volume of space-based photometric observations that must be analyzed in an efficient and unbia…
Identifying Exoplanets with Deep Learning II: Two New Super-Earths Uncovered by a Neural Network in K2 Data
Anne Dattilo, Andrew Vanderburg, Christopher J. Shallue +10
For years, scientists have used data from NASA's Kepler Space Telescope to look for and discover thousands of transiting exoplanets. In its extended K2 mission, Kepler observed sta…
Measuring the Effects of Data Parallelism on Neural Network Training
Christopher J. Shallue, Jaehoon Lee, Joseph Antognini +3
Recent hardware developments have dramatically increased the scale of data parallelism available for neural network training. Among the simplest ways to harness next-generation har…
Embedding Text in Hyperbolic Spaces
Bhuwan Dhingra, Christopher J. Shallue, Mohammad Norouzi +2
Natural language text exhibits hierarchical structure in a variety of respects. Ideally, we could incorporate our prior knowledge of this hierarchical structure into unsupervised l…
Identifying Exoplanets with Deep Learning: A Five Planet Resonant Chain around Kepler-80 and an Eighth Planet around Kepler-90
Christopher J. Shallue, Andrew Vanderburg
NASA's Kepler Space Telescope was designed to determine the frequency of Earth-sized planets orbiting Sun-like stars, but these planets are on the very edge of the mission's detect…
Permutation polynomials of finite fields
Christopher J. Shallue
Let be the finite field of elements. Then a \emph{permutation polynomial} (PP) of is a polynomial such that the associated…