Inference, Learning and Attention Mechanisms that Exploit and Preserve Sparsity in Convolutional Networks. - Timo Hackel; Mikhail Usvyatsov; Silvano Galliani; Jan Dirk Wegner; Konrad Schindler (CoRR, 2018)

Visual recognition in the wild by sampling deep similarity functions. - Mikhail Usvyatsov; Konrad Schindler (ICRA, 2019)

Indoor Scene Recognition in 3D. - Shengyu Huang; Mikhail Usvyatsov; Konrad Schindler (IROS, 2020)

Inference, Learning and Attention Mechanisms that Exploit and Preserve Sparsity in CNNs. - Timo Hackel; Mikhail Usvyatsov; Silvano Galliani; Jan D. Wegner; Konrad Schindler (Int. J. Comput. Vis., 2020)

Predator: Registration of 3D Point Clouds With Low Overlap. - Shengyu Huang; Zan Gojcic; Mikhail Usvyatsov; Andreas Wieser; Konrad Schindler (CVPR, 2021)

Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation. - Mikhail Usvyatsov; Anastasia Makarova; Rafael Ballester-Ripoll; Maxim V. Rakhuba; Andreas Krause 001; Konrad Schindler (ICCV, 2021)

T4DT: Tensorizing Time for Learning Temporal 3D Visual Data. - Mikhail Usvyatsov; Rafael Ballester; Lina Bashaeva; Konrad Schindler; Gonzalo Ferrer 001; Ivan V. Oseledets (BMVC, 2022)

tntorch: Tensor Network Learning with PyTorch. - Mikhail Usvyatsov; Rafael Ballester-Ripoll; Konrad Schindler (J. Mach. Learn. Res., 2022)

Potential and limitations of tensor methods for learning on visual data. - Mikhail Usvyatsov (2022)

TT-NF: Tensor Train Neural Fields. - Anton Obukhov; Mikhail Usvyatsov; Christos Sakaridis; Konrad Schindler; Luc Van Gool (IEEE J. Sel. Top. Signal Process., 2024)