1/9/2024 0 Comments Physics texpad![]() Matrix factorization gives automatic and continous sector assignments to stocks. LX Hayden, R Chachra, AA Alemi, PH Ginsparg, JP Sethna Canonical Sectors and Evolution of Firms in the US Stock Markets.Some rich decoder VAEs can magically focus on salient information. β-VAEs can retain label information even at high compression.More people should use the ArXiv as a dataset. On the Use of ArXiv as a Dataset ĬB Clement, M Bierbaum, KP O'Keeffe, AA Alemi.Variational Autoencoders with Tensorflow Probability Layers.Sometimes a worse decoder gives better representations. Dueling Decoders: Regularizing Variational Autoencoder Latent Spaces.Overview of recent advances in variationally bounding mutual information. On Variational Bounds of Mutual Information ī Poole, S Ozair, A van den Oord, AA Alemi, G Tucker.T Conte, E DeBenedictis, N Ganesh, T Hylton, JP Strachan, RS Williams, AA Alemi, L Altenberg, G Crooks, J Crutchfield, L del Rio, J Deutsch, M DeWeese, K Douglas, M Esposito, M Frank, R Fry, P Harsha, M Hill, C Kello, J Krichmar, S Kumar, SC Liu, S Lloyd, M Marsili, I Nemenman, A Nugent, N Packard, D Randall, P Sadowski, N Santhanam, R Shaw, A Stieg, E Stopnitzky, C Teuscher, C Watkins, D Wolpert, J Yang, Y YufikĪ position paper on the future of thermodynamic computing. Modern RNNs do not optimally capture predictive information in sequences. CEB Improves Model Robustness Ī class conditional version of VIB shows good robustness.While they seem complex, infinite ensembles of infinitely-wide networks are simple enough to enable tractable calculations of many information theoretic quantities. Information in Infinite Ensembles of Infinitely-Wide Networks.Most modern inference procedures can be rederived as a simple variational bound on a predictive information bottleneck objective. Variational Predictive Information Bottleneck.Simple to use python package for training infinitely wide neural networks. R Novak, L Xiao, J Hron, J Lee, AA Alemi, J Sohl-Dickstein, SS Schoenholz Neural Tangents: Fast and Easy Infinite Neural Networks in Python.The OpenKIM Processing Pipeline: A Cloud-Based Automatic Materials Property Computation Engine ĭS Karls, M Bierbaum, AA Alemi, RS Elliot, JP Sethna, EB Tadmor.Simple density-of-states inspired out of distribution detection. WR Morningstar, C Ham, AG Gallagher, B Lakshminarayanan, AA Alemi, JV Dillon Density of States Estimation for Out-of-Distribution Detection.Multisample bound that does better than Bayes at prediction for misspecified models. ![]()
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