107 citations · 163 across the 12 of their papers we have counts for
9 papers · 1 filter
Understanding Entropy Coding With Asymmetric Numeral Systems (ANS): a Statistician's Perspective
Robert Bamler
Entropy coding is the backbone data compression. Novel machine-learning based compression methods often use a new entropy coder called Asymmetric Numeral Systems (ANS) [Duda et al.…
User-Dependent Neural Sequence Models for Continuous-Time Event Data
Alex Boyd, Robert Bamler, Stephan Mandt +1
Continuous-time event data are common in applications such as individual behavior data, financial transactions, and medical health records. Modeling such data can be very challengi…
Extreme Classification via Adversarial Softmax Approximation
Robert Bamler, Stephan Mandt
Training a classifier over a large number of classes, known as 'extreme classification', has become a topic of major interest with applications in technology, science, and e-commer…
Tightening Bounds for Variational Inference by Revisiting Perturbation Theory
Robert Bamler, Cheng Zhang, Manfred Opper +1
Variational inference has become one of the most widely used methods in latent variable modeling. In its basic form, variational inference employs a fully factorized variational di…
A Quantum Field Theory of Representation Learning
Robert Bamler, Stephan Mandt
Continuous symmetries and their breaking play a prominent role in contemporary physics. Effective low-energy field theories around symmetry breaking states explain diverse phenomen…
Augmenting and Tuning Knowledge Graph Embeddings
Robert Bamler, Farnood Salehi, Stephan Mandt
Knowledge graph embeddings rank among the most successful methods for link prediction in knowledge graphs, i.e., the task of completing an incomplete collection of relational facts…