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Representation Learning

4,925 papers

Papers per year

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Papers

Efficient Expansion and Gradient Based Task Inference for Replay Free Incremental Learning WACV 2024
Few-Shot Shape Recognition by Learning Deep Shape-Aware Features WACV 2024
Leveraging Bitstream Metadata for Fast, Accurate, Generalized Compressed Video Quality Enhancement WACV 2024
ProxEdit: Improving Tuning-Free Real Image Editing With Proximal Guidance WACV 2024
Diverse Imagenet Models Transfer Better WACV 2024
Repetitive Action Counting With Motion Feature Learning WACV 2024
Hierarchical Diffusion Autoencoders and Disentangled Image Manipulation WACV 2024
Neural Image Compression Using Masked Sparse Visual Representation WACV 2024
Best of Both Worlds: Learning Arbitrary-Scale Blind Super-Resolution via Dual Degradation Representations and Cycle-Consistency WACV 2024
Hyperbolic VAE via Latent Gaussian Distributions NIPS 2023
Learning the Efficient Frontier NIPS 2023
Connecting Multi-modal Contrastive Representations NIPS 2023
Neural Fields with Hard Constraints of Arbitrary Differential Order NIPS 2023
Dynamically Masked Discriminator for GANs NIPS 2023
Data-Informed Geometric Space Selection NIPS 2023
Learning Large Graph Property Prediction via Graph Segment Training NIPS 2023
Moment Matching Denoising Gibbs Sampling NIPS 2023
ConDaFormer: Disassembled Transformer with Local Structure Enhancement for 3D Point Cloud Understanding NIPS 2023
Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry NIPS 2023
Hyper-Skin: A Hyperspectral Dataset for Reconstructing Facial Skin-Spectra from RGB Images NIPS 2023
Joint Feature and Differentiable $ k $-NN Graph Learning using Dirichlet Energy NIPS 2023
Labeling Neural Representations with Inverse Recognition NIPS 2023
Permutation Equivariant Neural Functionals NIPS 2023
Learning from Both Structural and Textual Knowledge for Inductive Knowledge Graph Completion NIPS 2023
Auxiliary Losses for Learning Generalizable Concept-based Models NIPS 2023