noise contrastive estimation

A Data-Augmented Contrastive Learning Approach to Nonparametric Density Estimation JMLR 2026 Bregman contrastive estimation as a general framework for learning unnormalized models: Efficiency, robustness and optimal noise UAI 2026 A Unified View on Learning Unnormalized Distributions via Noise-Contrastive Estimation ICML 2025 Deep Representation Learning for Forecasting Recursive and Multi-Relational Events in Temporal Networks AAAI 2025 Energy-Based Diffusion Language Models for Text Generation ICLR 2025 Score-Based Training for Energy-Based TTS Models Interspeech 2025 BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models ICML 2024 Mitigating the Impact of False Negative in Dense Retrieval with Contrastive Confidence Regularization AAAI 2024 Noise Contrastive Alignment of Language Models with Explicit Rewards NeurIPS 2024 Noise Contrastive Estimation-based Matching Framework for Low-Resource Security Attack Pattern Recognition EACL 2024 On the connection between Noise-Contrastive Estimation and Contrastive Divergence AISTATS 2024 Skill-aware Mutual Information Optimisation for Zero-shot Generalisation in Reinforcement Learning NeurIPS 2024 Your contrastive learning problem is secretly a distribution alignment problem NeurIPS 2024 Hierarchical Contrastive Learning for Temporal Point Processes AAAI 2023 Introducing Self-Supervised Phonetic Information for Text-Independent Speaker Verification Interspeech 2023 Learning Unnormalized Statistical Models via Compositional Optimization ICML 2023 Pitfalls of Gaussians as a noise distribution in NCE ICLR 2023 Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond NeurIPS 2023 Undirected Probabilistic Model for Tensor Decomposition NeurIPS 2023 Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model NeurIPS 2022 Analyzing and Improving the Optimization Landscape of Noise-Contrastive Estimation ICLR 2022 Do More Negative Samples Necessarily Hurt In Contrastive Learning? ICML 2022 Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects AISTATS 2022 Ranking Info Noise Contrastive Estimation: Boosting Contrastive Learning via Ranked Positives AAAI 2022 Self-Normalized Importance Sampling for Neural Language Modeling Interspeech 2022