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Generative Models

7,221 papers

Papers per year

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Papers

Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks ICML 2021
Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation ICML 2021
Learning from Nested Data with Ornstein Auto-Encoders ICML 2021
Riemannian Convex Potential Maps ICML 2021
Sliced Iterative Normalizing Flows ICML 2021
Intermediate Layer Optimization for Inverse Problems using Deep Generative Models ICML 2021
Measuring Robustness in Deep Learning Based Compressive Sensing ICML 2021
Bayesian Deep Learning via Subnetwork Inference ICML 2021
ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables ICML 2021
XOR-CD: Linearly Convergent Constrained Structure Generation ICML 2021
Coded-InvNet for Resilient Prediction Serving Systems ICML 2021
On Energy-Based Models with Overparametrized Shallow Neural Networks ICML 2021
Improved Contrastive Divergence Training of Energy-Based Models ICML 2021
Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network ICML 2021
Train simultaneously, generalize better: Stability of gradient-based minimax learners ICML 2021
Uncertainty Principles of Encoding GANs ICML 2021
Understanding Noise Injection in GANs ICML 2021
Oops I Took A Gradient: Scalable Sampling for Discrete Distributions ICML 2021
Hierarchical VAEs Know What They Don’t Know ICML 2021
Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes ICML 2021
Latent Programmer: Discrete Latent Codes for Program Synthesis ICML 2021
Generative Adversarial Transformers ICML 2021
Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions ICML 2021
Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization ICML 2021
Instance-Optimal Compressed Sensing via Posterior Sampling ICML 2021