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Steven Lang

2 accepted papers

2022

CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability

ICLR 2022poster

What is the state of the art in continual machine learning? Although a natural question for predominant static benchmarks, the notion to train systems in a lifelong manner entails a plethora of additional challenges with respect to set-up and evaluation. The latter have recently sparked a growing a…

2020

Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits

ICML 2020poster

Probabilistic circuits (PCs) are a promising avenue for probabilistic modeling, as they permit a wide range of exact and efficient inference routines. Recent “deep-learning-style” implementations of PCs strive for a better scalability, but are still difficult to train on real-world data, due to thei…