Alexander Bame Wiltschko
Alexander Bame Wiltschko
Staff Research Scientist, Google Brain
Verified email at
Cited by
Cited by
Composing graphical models with neural networks for structured representations and fast inference
MJ Johnson, DK Duvenaud, A Wiltschko, RP Adams, SR Datta
Advances in neural information processing systems 29, 2946-2954, 2016
Mapping sub-second structure in mouse behavior
AB Wiltschko, MJ Johnson, G Iurilli, RE Peterson, JM Katon, ...
Neuron 88 (6), 1121-1135, 2015
Selective activation of striatal fast-spiking interneurons during choice execution
GJ Gage, CR Stoetzner, AB Wiltschko, JD Berke
Neuron 67 (3), 466-479, 2010
Winner's curse? On pace, progress, and empirical rigor
D Sculley, J Snoek, A Wiltschko, A Rahimi
Wavelet filtering before spike detection preserves waveform shape and enhances single-unit discrimination
AB Wiltschko, GJ Gage, JD Berke
Journal of neuroscience methods 173 (1), 34-40, 2008
Machine learning approaches in cardiovascular imaging
M Henglin, G Stein, PV Hushcha, J Snoek, AB Wiltschko, S Cheng
Circulation: Cardiovascular Imaging 10 (10), e005614, 2017
Opposite effects of stimulant and antipsychotic drugs on striatal fast-spiking interneurons
AB Wiltschko, JR Pettibone, JD Berke
Neuropsychopharmacology 35 (6), 1261-1270, 2010
System and method for automatically discovering, characterizing, classifying and semi-automatically labeling animal behavior and quantitative phenotyping of behaviors in animals
SR Datta, AB Wiltschko
US Patent 9,317,743, 2016
Structured VAEs: Composing probabilistic graphical models and variational autoencoders
MJ Johnson, D Duvenaud, AB Wiltschko, SR Datta, RP Adams
arXiv preprint arXiv:1603.06277 2, 2016, 2016
Machine learning for scent: learning generalizable perceptual representations of small molecules
B Sanchez-Lengeling, JN Wei, BK Lee, RC Gerkin, A Aspuru-Guzik, ...
arXiv preprint arXiv:1910.10685, 2019
Revealing the structure of pharmacobehavioral space through motion sequencing
AB Wiltschko, T Tsukahara, A Zeine, R Anyoha, WF Gillis, JE Markowitz, ...
Nature neuroscience 23 (11), 1433-1443, 2020
Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming
B van Merrienboer, D Moldovan, AB Wiltschko
arXiv preprint arXiv:1809.09569, 2018
Autograph: Imperative-style coding with graph-based performance
D Moldovan, JM Decker, F Wang, AA Johnson, BK Lee, Z Nado, D Sculley, ...
arXiv preprint arXiv:1810.08061, 2018
Diagnosis of iron deficiency anemia using density-based fractionation of red blood cells
JW Hennek, AA Kumar, AB Wiltschko, MR Patton, SYR Lee, C Brugnara, ...
Lab on a Chip 16 (20), 3929-3939, 2016
Evaluating attribution for graph neural networks
B Sanchez-Lengeling, J Wei, B Lee, E Reif, P Wang, WW Qian, ...
Advances in neural information processing systems 33, 2020
Winner’s curse
D Sculley, J Snoek, A Wiltschko, A Rahimi
On pace, progress, and empirical rigor, 2018
Devices and methods for analyzing rodent behavior
CJ Woolf, DP Roberson, AB Wiltschko, SR Datta
US Patent 10,238,085, 2019
Avoiding a tragedy of the commons in the peer review process
D Sculley, J Snoek, A Wiltschko
arXiv preprint arXiv:1901.06246, 2018
Tangent: Automatic differentiation using source code transformation in Python
B van MerriŽnboer, AB Wiltschko, D Moldovan
arXiv preprint arXiv:1711.02712, 2017
Composing graphical models with neural networks for structured representations and fast inference. arXiv. org
MJ Johnson, D Duvenaud, AB Wiltschko, SR Datta, RP Adams
March, 2016
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