Search Results - Ajanthan, Thalaiyasingam

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  1. 1
    DGPose: Deep Generative Models for Human Body Analysis

    DGPose: Deep Generative Models for Human Body Analysis by de Bem, Rodrigo, Ghosh, Arnab, Ajanthan, Thalaiyasingam, Miksik, Ondrej, Boukhayma, Adnane, Siddharth, N., Torr, Philip

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  2. 2
    Bidirectionally self-normalizing neural networks

    Bidirectionally self-normalizing neural networks by Lu, Yao, Gould, Stephen, Ajanthan, Thalaiyasingam

    Published in Neural networks
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  3. 3
    Memory Efficient Max Flow for Multi-Label Submodular MRFs

    Memory Efficient Max Flow for Multi-Label Submodular MRFs by Ajanthan, Thalaiyasingam, Hartley, Richard, Salzmann, Mathieu

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  4. 4
    Few-shot Weakly-Supervised Object Detection via Directional Statistics

    Few-shot Weakly-Supervised Object Detection via Directional Statistics by Shaban, Amirreza, Rahimi, Amir, Ajanthan, Thalaiyasingam, Boots, Byron, Hartley, Richard

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  5. 5
    Proximal Mean-Field for Neural Network Quantization

    Proximal Mean-Field for Neural Network Quantization by Ajanthan, Thalaiyasingam, Dokania, Puneet, Hartley, Richard, Torr, Philip

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  6. 6
    Improved Gradient-Based Adversarial Attacks for Quantized Networks

    Improved Gradient-Based Adversarial Attacks for Quantized Networks by Gupta, Kartik, Ajanthan, Thalaiyasingam

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  7. 7
    Self-Supervision Improves Diffusion Models for Tabular Data Imputation

    Self-Supervision Improves Diffusion Models for Tabular Data Imputation by Liu, Yixin, Ajanthan, Thalaiyasingam, Husain, Hisham, Nguyen, Vu

    Published in arXiv.org
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  8. 8
    Accept the Modality Gap: An Exploration in the Hyperbolic Space

    Accept the Modality Gap: An Exploration in the Hyperbolic Space by Ramasinghe, Sameera, Shevchenko, Violetta, Avraham, Gil, Thalaiyasingam, Ajanthan

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  9. 9
    Improved Gradient based Adversarial Attacks for Quantized Networks

    Improved Gradient based Adversarial Attacks for Quantized Networks by Gupta, Kartik, Ajanthan, Thalaiyasingam

    Published in arXiv.org
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  10. 10
    Guiding Neural Collapse: Optimising Towards the Nearest Simplex Equiangular Tight Frame

    Guiding Neural Collapse: Optimising Towards the Nearest Simplex Equiangular Tight Frame by Markou, Evan, Ajanthan, Thalaiyasingam, Gould, Stephen

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  11. 11
    RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs

    RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs by Xu, Zhiwei, Ajanthan, Thalaiyasingam, Vineet, Vibhav, Hartley, Richard

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  12. 12
    Bidirectionally Self-Normalizing Neural Networks

    Bidirectionally Self-Normalizing Neural Networks by Lu, Yao, Gould, Stephen, Ajanthan, Thalaiyasingam

    Published in arXiv.org
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  13. 13
    Adaptive Cross Batch Normalization for Metric Learning

    Adaptive Cross Batch Normalization for Metric Learning by Ajanthan, Thalaiyasingam, Ma, Matt, van den Hengel, Anton, Gould, Stephen

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  14. 14
    Learning Visual Hierarchies with Hyperbolic Embeddings

    Learning Visual Hierarchies with Hyperbolic Embeddings by Wang, Ziwei, Ramasinghe, Sameera, Xu, Chenchen, Monteil, Julien, Bazzani, Loris, Ajanthan, Thalaiyasingam

    Published in arXiv.org
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  15. 15
    Understanding and Improving the Role of Projection Head in Self-Supervised Learning

    Understanding and Improving the Role of Projection Head in Self-Supervised Learning by Gupta, Kartik, Ajanthan, Thalaiyasingam, van den Hengel, Anton, Gould, Stephen

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  16. 16
    Refining Semantic Segmentation with Superpixel by Transparent Initialization and Sparse Encoder

    Refining Semantic Segmentation with Superpixel by Transparent Initialization and Sparse Encoder by Xu, Zhiwei, Ajanthan, Thalaiyasingam, Hartley, Richard

    Published in arXiv.org
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  17. 17
    Fast and Differentiable Message Passing on Pairwise Markov Random Fields

    Fast and Differentiable Message Passing on Pairwise Markov Random Fields by Xu, Zhiwei, Ajanthan, Thalaiyasingam, Hartley, Richard

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  18. 18
    Understanding the Effects of Data Parallelism and Sparsity on Neural Network Training

    Understanding the Effects of Data Parallelism and Sparsity on Neural Network Training by Lee, Namhoon, Ajanthan, Thalaiyasingam, Torr, Philip H S, Jaggi, Martin

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  19. 19
    Few-shot Weakly-Supervised Object Detection via Directional Statistics

    Few-shot Weakly-Supervised Object Detection via Directional Statistics by Shaban, Amirreza, Rahimi, Amir, Ajanthan, Thalaiyasingam, Boots, Byron, Hartley, Richard

    Published in arXiv.org
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  20. 20
    RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs

    RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs by Xu, Zhiwei, Ajanthan, Thalaiyasingam, Vibhav Vineet, Hartley, Richard

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