probability distribution

Particle Dual Averaging: Optimization of Mean Field Neural Network with Global Convergence Rate Analysis NeurIPS 2021 Riemannian Convex Potential Maps ICML 2021 Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks ICML 2021 Sinusoidal Flow: A Fast Invertible Autoregressive Flow ACML 2021 Sliced Iterative Normalizing Flows ICML 2021 Testing Probabilistic Circuits NeurIPS 2021 Unbalanced minibatch Optimal Transport; applications to Domain Adaptation ICML 2021 Wasserstein Barycenter for Multi-Source Domain Adaptation CVPR 2021 When in Doubt: Improving Classification Performance with Alternating Normalization EMNLP 2021 Why did the distribution change? AISTATS 2021 Adaptive Sampling for Estimating Probability Distributions ICML 2020 Aggregation of Perspectives Using the Constellations Approach to Probabilistic Argumentation AAAI 2020 A Universal Approximation Theorem of Deep Neural Networks for Expressing Probability Distributions NeurIPS 2020 Compositional Visual Generation with Energy Based Models NeurIPS 2020 Continuous Regularized Wasserstein Barycenters NeurIPS 2020 Do you have the right scissors? Tailoring Pre-trained Language Models via Monte-Carlo Methods ACL 2020 Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs NeurIPS 2020 Fˆ2-Softmax: Diversifying Neural Text Generation via Frequency Factorized Softmax EMNLP 2020 Few-Shot Learning of Part-Specific Probability Space for 3D Shape Segmentation CVPR 2020 Gaussianization Flows AISTATS 2020 Generalized Entropy Regularization or: There’s Nothing Special about Label Smoothing ACL 2020 Generating and Exploiting Probabilistic Monocular Depth Estimates CVPR 2020 How to Grow a (Product) Tree: Personalized Category Suggestions for eCommerce Type-Ahead ACL 2020 Just Add Functions: A Neural-Symbolic Language Model AAAI 2020 Kernelized Wasserstein Natural Gradient ICLR 2020