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Methodology
← Learning Types
Machine Learning
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Learning Types
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Representation Learning
2843 directly classified papers
Papers per year
2002: 1
2005: 2
2006: 5
2007: 11
2008: 12
2009: 10
2010: 6
2011: 6
2012: 30
2013: 36
2014: 34
2015: 20
2016: 42
2017: 82
2018: 128
2019: 189
2020: 266
2021: 279
2022: 382
2023: 358
2024: 451
2025: 486
2026: 7
Papers
Counterfactual Maximum Likelihood Estimation for Training Deep Networks
NIPS 2021
Improving Compositionality of Neural Networks by Decoding Representations to Inputs
NIPS 2021
Curriculum Disentangled Recommendation with Noisy Multi-feedback
NIPS 2021
Multi-VAE: Learning Disentangled View-Common and View-Peculiar Visual Representations for Multi-View Clustering
ICCV 2021
When Computational Representation Meets Neuroscience: A Survey on Brain Encoding and Decoding
IJCAI 2021
LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
INTERSPEECH 2021
Uncertainty-Aware Multi-View Representation Learning
AAAI 2021
Attentive Neural Point Processes for Event Forecasting
AAAI 2021
Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning
AAAI 2021
Relation-aware Graph Attention Model with Adaptive Self-adversarial Training
AAAI 2021
Identity-aware Graph Neural Networks
AAAI 2021
Likelihood-Based Diverse Sampling for Trajectory Forecasting
ICCV 2021
Learning Target Candidate Association To Keep Track of What Not To Track
ICCV 2021
Towards Better Explanations of Class Activation Mapping
ICCV 2021
Structured Visual Search via Composition-Aware Learning
WACV 2021
Scalable Graph Networks for Particle Simulations
AAAI 2021
Improved Mutual Information Estimation
AAAI 2021
Learning Dynamics Models with Stable Invariant Sets
AAAI 2021
Deep Wasserstein Graph Discriminant Learning for Graph Classification
AAAI 2021
Partial-Label and Structure-constrained Deep Coupled Factorization Network
AAAI 2021
SMART: A Situation Model for Algebra Story Problems via Attributed Grammar
AAAI 2021
Have We Solved The Hard Problem? It’s Not Easy! Contextual Lexical Contrast as a Means to Probe Neural Coherence
AAAI 2021
Circles are like Ellipses, or Ellipses are like Circles? Measuring the Degree of Asymmetry of Static and Contextual Word Embeddings and the Implications to Representation Learning
AAAI 2021
Detecting Lexical Semantic Change across Corpora with Smooth Manifolds (Student Abstract)
AAAI 2021
Semi-Discrete Social Recommendation (Student Abstract)
AAAI 2021
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