Yanda's Random Notes

Search

SearchSearch
          • Attention is all you need
          • Barlow Twins
          • BEV baseline
          • BEVFormer
          • CenterNet (Keypoint Triplets)
          • CenterNet (Objects as Points)
          • CenterTrack
          • Class-Balanced Loss
          • CLIP
          • ConvNext
          • CornerNet
          • DETR
          • e-OSVOS
          • Feature Pyramid Networks
          • Focal loss (RetinaNet)
          • MAML
          • Masked Autoencoders (MAE)
          • Mixup
          • MLP Mixer
          • Papers Kanban
          • Reptile
          • SoDA
          • SpotNet
          • SSD
          • Swin Transformer
          • Two Step CCA
          • Uncertainty based learnable weighting
          • Variational Autoencoder (VAE)
          • Vision Transformer (ViT)
        • Contrastive learning
        • Meta Learning
        • Video Object Segmentation
        • zero shot learning
        • Getting started with Nix, 2023 Edition
        • On nix-darwin
        • Fundamentals of Unconstrained optimization
        • Extended Kalman Filter
        • Information Filter
        • Intro and Bayes Filters
        • Kalman Filter
        • Unscented Kalman Filter
        • 01_getting_started
        • 02_programming_a_guessing_game
        • 03_common_programming_concepts
        • 04_understand_ownership
        • 05_using_structs_to_structure_related_data
        • 06_enums_and_pattern_matching
        • 07_managing_growing_projects_with_packages_crates_and_modules
        • 08_common_collections
        • 09_error_handling
        • 10_generic_types_traits_and_lifetimes
        • 11_write_automated_tests
        • 12_io_project
        • 13_functional_language_features_iterators_and_closures
        • 14_more_about_cargo_and_crates_io
        • 15_smart_pointers
        • 16_fearless_concurrency
        • 17_object_oriented_programming_features_of_rust
        • 18_patterns_and_matching
        • 19_advanced_features
        • Tesla AI Day
    Home

    ❯

    ML

    ❯

    papers

    ❯

    Papers Kanban

    Papers Kanban

    Jun 19, 2023, 1 min read

    Finished §

    Complete

    • CLIP
    • CornerNet
    • FPN
    • SSD
    • ViT
    • Focal loss
    • CenterNet (Keypoint Triplets)
    • SpotNet
    • BEV baseline
    • e-OSVOS
    • Mixup
    • DETR
    • BEVFormer
    • MLP Mixer
    • Swin Transformer
    • ConvNext

    Planned §

    • Segment Anything
    • Deformable Attention
    • DEFT

    Backlog §

    • YOLO families
    • RCNN families

    Graph View

    • Finished
    • Planned
    • Backlog

    Backlinks

    • No backlinks found

    Created with Quartz v4.1.5, © 2024