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https://openreview.net/forum?id=Bk0MRI5lg Bridging Nonlinearities and Stochastic Regularizers with Gaussian Error Linear Units | OpenReview A Competitor of ReLUs and ELUs with a Probabilistic Underpinning bridging stochastic regularizers https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/keras/regularizers Module: tf.keras.regularizers | TensorFlow v2.3.0 module tf keras regularizers tensorflow https://www.tensorflow.org/versions/r2.2/api_docs/python/tf/keras/regularizers Module: tf.keras.regularizers | TensorFlow v2.2.0 module tf keras regularizers tensorflow https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/keras/regularizers Module: tf.keras.regularizers | TensorFlow v2.9.3 Built-in regularizers. module tf keras regularizers tensorflow https://openreview.net/forum?id=ayo_Z9U1kK LSGANs with Gradient Regularizers are Smooth High-dimensional Interpolators | OpenReview We link the optimal discriminator in gradient-regularized LSGANs to interpolation. Enforcing interpolation-based image-space penalties on LSGAN results in an... high dimensional gradient regularizers smooth interpolators https://www.tensorflow.org/versions/r2.10/api_docs/python/tf/keras/regularizers/l1_l2 tf.keras.regularizers.l1_l2 | TensorFlow v2.10.1 Create a regularizer that applies both L1 and L2 penalties. l1 l2 tf keras regularizers tensorflow https://deepai.org/publication/gans-with-variational-entropy-regularizers-applications-in-mitigating-the-mode-collapse-issue GANs with Variational Entropy Regularizers: Applications in Mitigating the Mode-Collapse Issue |... Sep 24, 2020 - 09/24/20 - Building on the success of deep learning, Generative Adversarial Networks (GANs) provide a modern approach to learn a probability ... https://www.tensorflow.org/versions/r2.8/api_docs/python/tf/keras/regularizers/get tf.keras.regularizers.get | TensorFlow v2.8.4 Retrieve a regularizer instance from a config or identifier. tf keras regularizers get tensorflow https://www.tensorflow.org/versions/r2.11/api_docs/python/tf/keras/regularizers/get tf.keras.regularizers.get | TensorFlow v2.11.1 Retrieve a regularizer instance from a config or identifier. tf keras regularizers get tensorflow https://openreview.net/forum?id=8SEJ8AT_6Dl Minimax Optimal Quantile and Semi-Adversarial Regret via Root-Logarithmic Regularizers | OpenReview Quantile (and, more generally, KL) regret bounds, such as those achieved by NormalHedge (Chaudhuri, Freund, and Hsu 2009) and its variants, relax the goal of... https://openreview.net/forum?id=32oLu7d1vlT&referrer=%5Bthe%20profile%20of%20Martin%20Burger%5D(%2Fprofile%3Fid%3D~Martin_Burger1) Learning convex regularizers satisfying the variational source condition for inverse problems |... Variational regularization has remained one of the most successful approaches for reconstruction in imaging inverse problems for several decades. With the... learning convex regularizers satisfying https://www.tensorflow.org/versions/r2.12/api_docs/python/tf/keras/regularizers/get tf.keras.regularizers.get | TensorFlow v2.12.1 Retrieve a regularizer instance from a config or identifier. tf keras regularizers get tensorflow https://arxiv.org/abs/1206.6455 [1206.6455] Regularizers versus Losses for Nonlinear Dimensionality Reduction: A Factored View with... Abstract page for arXiv paper 1206.6455: Regularizers versus Losses for Nonlinear Dimensionality Reduction: A Factored View with New Convex Relaxations https://www.ias.edu/video/theorydeeplearning/2019/1017-TengyuMa Designing Explicit Regularizers for Deep Models | Videos | Institute for Advanced Study Oct 17, 2019 - https://www.ias.edu/math/wtdl models videos designing explicit regularizers deep