Published in The British Machine Vision Conference (BMVC) 2021, 2021
We present the first one-pass-algorithm for generating semantically meaningful counterfactual image examples.
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Published in arXiv, 2021
The paper presents a fast algorithm, FastFID, for computing the Fréchet Inception Distance (FID) on a small bacth. The algorithm allows monitoring the FID of GANs during training and even training GANs with FID as a loss.
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Published in NeurIPS 2020 (Spotlight), 2020
The paper presents a fast parallel algorithm suited for GPUs which works for a reparameterization of an SVD in a Houdsholder decomposition. We demonstrate high speed-ups in practice.
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Published in arXiv, 2020
We prove that compositions of many Householder reflections can be replaced with one “auxillary reflection.” Such replacement yields higher GPU utilization and thus speeds up training and inference.
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Published in arXiv, 2020
We present ideas on how to improve the highly popular explanation method LIME.
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Published in ICML Workshop on Invertyible Neural Networks, Normalizing Flows, and Explicit Likelihood Models, 2020
The paper presents a fast parallel algorithm for multiplying an orthogonal matrix, parameterized by a sequence of Householder matrices, with an input vector
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