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← Core Methods
Machine Learning
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Core Methods
›
Representation Learning
18,863 papers
Papers per year
2000: 2
2001: 4
2002: 2
2003: 18
2004: 4
2005: 9
2006: 62
2007: 61
2008: 74
2009: 73
2010: 96
2011: 103
2012: 131
2013: 283
2014: 255
2015: 295
2016: 426
2017: 691
2018: 1066
2019: 1798
2020: 1830
2021: 2207
2022: 2109
2023: 2560
2024: 2177
2025: 1926
2026: 601
Papers
Cross-Linguistic Phonological Similarity Analysis in Sign Languages Using HamNoSys
AACL 2025
Disentangling Mathematical Reasoning in LLMs: A Methodological Investigation of Internal Mechanisms
EMNLP 2025
How does PDE order affect the convergence of PINNs?
NIPS 2024
Mixtures of Experts for Audio-Visual Learning
NIPS 2024
Learning Place Cell Representations and Context-Dependent Remapping
NIPS 2024
Collaborative Cognitive Diagnosis with Disentangled Representation Learning for Learner Modeling
NIPS 2024
Physics-Informed Regularization for Domain-Agnostic Dynamical System Modeling
NIPS 2024
Improving Sparse Decomposition of Language Model Activations with Gated Sparse Autoencoders
NIPS 2024
Towards Understanding How Transformers Learn In-context Through a Representation Learning Lens
NIPS 2024
Prospective Representation Learning for Non-Exemplar Class-Incremental Learning
NIPS 2024
Differentiable Modal Synthesis for Physical Modeling of Planar String Sound and Motion Simulation
NIPS 2024
Unified Lexical Representation for Interpretable Visual-Language Alignment
NIPS 2024
AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases
NIPS 2024
einspace: Searching for Neural Architectures from Fundamental Operations
NIPS 2024
A Walsh Hadamard Derived Linear Vector Symbolic Architecture
NIPS 2024
Mutual Information Estimation via Normalizing Flows
NIPS 2024
UniSDF: Unifying Neural Representations for High-Fidelity 3D Reconstruction of Complex Scenes with Reflections
NIPS 2024
NeuralSolver: Learning Algorithms For Consistent and Efficient Extrapolation Across General Tasks
NIPS 2024
HyperLogic: Enhancing Diversity and Accuracy in Rule Learning with HyperNets
NIPS 2024
Flexible Context-Driven Sensory Processing in Dynamical Vision Models
NIPS 2024
Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization
NIPS 2024
LAM3D: Large Image-Point Clouds Alignment Model for 3D Reconstruction from Single Image
NIPS 2024
HORSE: Hierarchical Representation for Large-Scale Neural Subset Selection
NIPS 2024
Segment, Shuffle, and Stitch: A Simple Layer for Improving Time-Series Representations
NIPS 2024
Learning Representations for Hierarchies with Minimal Support
NIPS 2024
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