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Manifold coordinates with physical meaning via Riemannian geometry [1]

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Algorithmic Bias Control in Deep learning [2]

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Frequency principle in understanding the generalization of deep learning and the depth effect [3]

  • Read more about Frequency principle in understanding the generalization of deep learning and the depth effect [3]

Optimally weighted loss functions for solving PDEs with Neural Networks: theory, practice and improvements [4]

  • Read more about Optimally weighted loss functions for solving PDEs with Neural Networks: theory, practice and improvements [4]

Generation by Decomposition for Handwritten Text and 3D Shapes [5]

  • Read more about Generation by Decomposition for Handwritten Text and 3D Shapes [5]

Regularization by Denoising via Fixed-Point Projection (RED-PRO) [6]

  • Read more about Regularization by Denoising via Fixed-Point Projection (RED-PRO) [6]

Cancelled [7]

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On Linear Identifiability of Learned Representations [8]

  • Read more about On Linear Identifiability of Learned Representations [8]

Active Community Detection with Maximal Expected Model Change [9]

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-Statistics joint seminar: Tensor Decompositions in Machine Learning [10]

  • Read more about -Statistics joint seminar: Tensor Decompositions in Machine Learning [10]
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Links
[1] https://calendar.math.yale.edu/event/manifold-coordinates-physical-meaning-riemannian-geometry [2] https://calendar.math.yale.edu/event/algorithmic-bias-control-deep-learning [3] https://calendar.math.yale.edu/event/frequency-principle-understanding-generalization-deep-learning-and-depth-effect [4] https://calendar.math.yale.edu/event/optimally-weighted-loss-functions-solving-pdes-neural-networks-theory-practice-and [5] https://calendar.math.yale.edu/event/generation-decomposition-handwritten-text-and-3d-shapes [6] https://calendar.math.yale.edu/event/regularization-denoising-fixed-point-projection-red-pro [7] https://calendar.math.yale.edu/event/cancelled-11 [8] https://calendar.math.yale.edu/event/linear-identifiability-learned-representations [9] https://calendar.math.yale.edu/event/active-community-detection-maximal-expected-model-change [10] https://calendar.math.yale.edu/event/statistics-joint-seminar-tensor-decompositions-machine-learning [11] https://calendar.math.yale.edu/seminars/applied-mathematics [12] https://calendar.math.yale.edu/seminars/applied-mathematics?page=7 [13] https://calendar.math.yale.edu/seminars/applied-mathematics?page=4 [14] https://calendar.math.yale.edu/seminars/applied-mathematics?page=5 [15] https://calendar.math.yale.edu/seminars/applied-mathematics?page=6 [16] https://calendar.math.yale.edu/seminars/applied-mathematics?page=9 [17] https://calendar.math.yale.edu/seminars/applied-mathematics?page=10 [18] https://calendar.math.yale.edu/seminars/applied-mathematics?page=11 [19] https://calendar.math.yale.edu/seminars/applied-mathematics?page=12 [20] https://calendar.math.yale.edu/seminars/applied-mathematics?page=28