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<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="4.3.2">Jekyll</generator><link href="http://0.0.0.0:4000/feed.xml" rel="self" type="application/atom+xml" /><link href="http://0.0.0.0:4000/" rel="alternate" type="text/html" /><updated>2024-10-30T11:57:18+00:00</updated><id>http://0.0.0.0:4000/feed.xml</id><title type="html">MATH+ML+X Lab</title><subtitle>Welcome to the Math+ML+X Lab!</subtitle><entry><title type="html">Mamba Neural Operator: Who Wins? Transformers vs. State-Space Models for PDEs</title><link href="http://0.0.0.0:4000/2024/10/01/mambano.html" rel="alternate" type="text/html" title="Mamba Neural Operator: Who Wins? Transformers vs. State-Space Models for PDEs" /><published>2024-10-01T00:00:00+00:00</published><updated>2024-10-28T18:15:30+00:00</updated><id>http://0.0.0.0:4000/2024/10/01/mambano</id><content type="html" xml:base="http://0.0.0.0:4000/2024/10/01/mambano.html"><![CDATA[<p>[P] — Mamba Neural Operator: Who Wins? Transformers vs. State-Space Models for PDEs<br />
CW Cheng, J Huang, Y Zhang, G Yang, C</p>
<ul>
<li><a href="https://arxiv.org/search/cs?searchtype=author&query=Schonlieb,+C">–</a></li>
<li><a href="https://arxiv.org/pdf/2410.02113">Arxiv-Link </a></li>
</ul>]]></content><author><name>CW Cheng, J Huang, Y Zhang, G Yang, C</name></author><summary type="html"><![CDATA[[P] — Mamba Neural Operator: Who Wins? Transformers vs. State-Space Models for PDEs CW Cheng, J Huang, Y Zhang, G Yang, C – Arxiv-Link ]]></summary><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/10/mambano.png" /><media:content medium="image" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/10/mambano.png" xmlns:media="http://search.yahoo.com/mrss/" /></entry><entry><title type="html">Inertial Proximal Difference-of-Convex Algorithm with Convergent Bregman Plug-and-Play for Nonconvex Imaging</title><link href="http://0.0.0.0:4000/2024/09/01/bregmanpnp.html" rel="alternate" type="text/html" title="Inertial Proximal Difference-of-Convex Algorithm with Convergent Bregman Plug-and-Play for Nonconvex Imaging" /><published>2024-09-01T00:00:00+00:00</published><updated>2024-10-28T18:15:30+00:00</updated><id>http://0.0.0.0:4000/2024/09/01/bregmanpnp</id><content type="html" xml:base="http://0.0.0.0:4000/2024/09/01/bregmanpnp.html"><![CDATA[<p>[P] — Inertial Proximal Difference-of-Convex Algorithm with Convergent Bregman Plug-and-Play for Nonconvex Imaging<br />
TC Chow, C Huang, Z Wu, T Zeng and</p>
<ul>
<li><a href="https://arxiv.org/pdf/2409.03262v1">Arxiv-Link </a></li>
</ul>]]></content><author><name>TC Chow, C Huang, Z Wu, T Zeng and</name></author><summary type="html"><![CDATA[[P] — Inertial Proximal Difference-of-Convex Algorithm with Convergent Bregman Plug-and-Play for Nonconvex Imaging TC Chow, C Huang, Z Wu, T Zeng and Arxiv-Link ]]></summary><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/09/bregmanpnp.png" /><media:content medium="image" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/09/bregmanpnp.png" xmlns:media="http://search.yahoo.com/mrss/" /></entry><entry><title type="html">Learning Task-Specific Sampling Strategy for Sparse-View CT Reconstruction</title><link href="http://0.0.0.0:4000/2024/09/01/screenshot-2024-09-10-at-17.30.12.html" rel="alternate" type="text/html" title="Learning Task-Specific Sampling Strategy for Sparse-View CT Reconstruction" /><published>2024-09-01T00:00:00+00:00</published><updated>2024-10-28T18:15:30+00:00</updated><id>http://0.0.0.0:4000/2024/09/01/screenshot-2024-09-10-at-17.30.12</id><content type="html" xml:base="http://0.0.0.0:4000/2024/09/01/screenshot-2024-09-10-at-17.30.12.html"><![CDATA[<p>[P] — Learning Task-Specific Sampling Strategy for Sparse-View CT Reconstruction<br />
L Yang, J Huang, Y Fang,</p>
<ul>
<li><a href="https://arxiv.org/pdf/2409.01544">Arxiv-Link </a></li>
</ul>]]></content><author><name>L Yang, J Huang, Y Fang,</name></author><summary type="html"><![CDATA[[P] — Learning Task-Specific Sampling Strategy for Sparse-View CT Reconstruction L Yang, J Huang, Y Fang, Arxiv-Link ]]></summary><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/09/screenshot-2024-09-10-at-17.30.12.png" /><media:content medium="image" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/09/screenshot-2024-09-10-at-17.30.12.png" xmlns:media="http://search.yahoo.com/mrss/" /></entry><entry><title type="html">Contrastive Learning with Dynamic Localized Repulsion for Brain Age Prediction on 3D Stiffness Maps</title><link href="http://0.0.0.0:4000/2024/09/01/screenshot-2024-09-19-at-19.00.01.html" rel="alternate" type="text/html" title="Contrastive Learning with Dynamic Localized Repulsion for Brain Age Prediction on 3D Stiffness Maps" /><published>2024-09-01T00:00:00+00:00</published><updated>2024-10-28T18:15:30+00:00</updated><id>http://0.0.0.0:4000/2024/09/01/screenshot-2024-09-19-at-19.00.01</id><content type="html" xml:base="http://0.0.0.0:4000/2024/09/01/screenshot-2024-09-19-at-19.00.01.html"><![CDATA[<p>[P] — Contrastive Learning with Dynamic Localized Repulsion for Brain Age Prediction on 3D Stiffness Maps<br />
J Trauble, L Hiscox, C Johnson, C</p>
<ul>
<li><a href="https://arxiv.org/search/cs?searchtype=author&query=Schonlieb,+C">–</a></li>
<li><a href="https://arxiv.org/pdf/2408.00527">Arxiv-Link </a></li>
</ul>]]></content><author><name>J Trauble, L Hiscox, C Johnson, C</name></author><summary type="html"><![CDATA[[P] — Contrastive Learning with Dynamic Localized Repulsion for Brain Age Prediction on 3D Stiffness Maps J Trauble, L Hiscox, C Johnson, C – Arxiv-Link ]]></summary><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/09/screenshot-2024-09-19-at-19.00.01.png" /><media:content medium="image" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/09/screenshot-2024-09-19-at-19.00.01.png" xmlns:media="http://search.yahoo.com/mrss/" /></entry><entry><title type="html">Semi-Supervised Video Desnowing Network via Temporal Decoupling Experts and Distribution-Driven Contrastive Regularization</title><link href="http://0.0.0.0:4000/2024/07/01/eccv24.html" rel="alternate" type="text/html" title="Semi-Supervised Video Desnowing Network via Temporal Decoupling Experts and Distribution-Driven Contrastive Regularization" /><published>2024-07-01T00:00:00+00:00</published><updated>2024-10-28T18:15:30+00:00</updated><id>http://0.0.0.0:4000/2024/07/01/eccv24</id><content type="html" xml:base="http://0.0.0.0:4000/2024/07/01/eccv24.html"><![CDATA[<p>[C] — Semi-Supervised Video Desnowing Network via Temporal Decoupling Experts and Distribution-Driven Contrastive Regularization<br />
H Wu, Y Yang,</p>]]></content><author><name>H Wu, Y Yang,</name></author><summary type="html"><![CDATA[[C] — Semi-Supervised Video Desnowing Network via Temporal Decoupling Experts and Distribution-Driven Contrastive Regularization H Wu, Y Yang,]]></summary><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/07/eccv24.gif" /><media:content medium="image" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/07/eccv24.gif" xmlns:media="http://search.yahoo.com/mrss/" /></entry><entry><title type="html">Optimised Propainter for Video Diminished Reality Inpainting</title><link href="http://0.0.0.0:4000/2024/07/01/isbi2024.html" rel="alternate" type="text/html" title="Optimised Propainter for Video Diminished Reality Inpainting" /><published>2024-07-01T00:00:00+00:00</published><updated>2024-10-28T18:15:30+00:00</updated><id>http://0.0.0.0:4000/2024/07/01/isbi2024</id><content type="html" xml:base="http://0.0.0.0:4000/2024/07/01/isbi2024.html"><![CDATA[<p>[C] — Optimised Propainter for Video Diminished Reality Inpainting<br />
P Li<em>, L Liu</em>, C</p>
<ul>
<li><a href="https://arxiv.org/search/cs?searchtype=author&query=Schonlieb,+C">–</a></li>
<li><a href="https://arxiv.org/pdf/2406.02287">Arxiv-Link</a></li>
</ul>]]></content><author><name>P Li*, L Liu*, C</name></author><summary type="html"><![CDATA[[C] — Optimised Propainter for Video Diminished Reality Inpainting P Li, L Liu, C – Arxiv-Link]]></summary><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/07/isbi2024.png" /><media:content medium="image" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/07/isbi2024.png" xmlns:media="http://search.yahoo.com/mrss/" /></entry><entry><title type="html">Enhancing Global Sensitivity and Uncertainty Quantification in Medical Image Reconstruction with Monte Carlo Arbitrary-Masked Mamba</title><link href="http://0.0.0.0:4000/2024/07/01/mambamri2.html" rel="alternate" type="text/html" title="Enhancing Global Sensitivity and Uncertainty Quantification in Medical Image Reconstruction with Monte Carlo Arbitrary-Masked Mamba" /><published>2024-07-01T00:00:00+00:00</published><updated>2024-10-28T18:15:30+00:00</updated><id>http://0.0.0.0:4000/2024/07/01/mambamri2</id><content type="html" xml:base="http://0.0.0.0:4000/2024/07/01/mambamri2.html"><![CDATA[<p>[J] — Enhancing Global Sensitivity and Uncertainty Quantification in Medical Image Reconstruction with Monte Carlo Arbitrary-Masked Mamba<br />
J Huang, L Yang, … ,</p>
<ul>
<li><a href="https://arxiv.org/search/cs?searchtype=author&query=Schonlieb,+C">–</a></li>
<li><a href="https://arxiv.org/pdf/2405.17659">Arxiv-Link </a></li>
<li><a href="https://www.sciencedirect.com/science/article/pii/S1361841524002597?via%3Dihub">Journal</a></li>
</ul>]]></content><author><name>J Huang, L Yang, … ,</name></author><summary type="html"><![CDATA[[J] — Enhancing Global Sensitivity and Uncertainty Quantification in Medical Image Reconstruction with Monte Carlo Arbitrary-Masked Mamba J Huang, L Yang, … , – Arxiv-Link Journal]]></summary><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/07/mambamri2.png" /><media:content medium="image" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/07/mambamri2.png" xmlns:media="http://search.yahoo.com/mrss/" /></entry><entry><title type="html">Training-Free Feature Reconstruction with Sparse Optimization for Vision-Language Models</title><link href="http://0.0.0.0:4000/2024/07/01/mm24b.html" rel="alternate" type="text/html" title="Training-Free Feature Reconstruction with Sparse Optimization for Vision-Language Models" /><published>2024-07-01T00:00:00+00:00</published><updated>2024-10-28T18:15:30+00:00</updated><id>http://0.0.0.0:4000/2024/07/01/mm24b</id><content type="html" xml:base="http://0.0.0.0:4000/2024/07/01/mm24b.html"><![CDATA[<p>[C] — Training-Free Feature Reconstruction with Sparse Optimization for Vision-Language Models<br />
Y Zhang, K Yu,</p>
<ul>
<li><a href="https://openreview.net/pdf/ae8f5590c7cfe5adc254e23bf5d29008274cabd3.pdf">Arxiv-Link</a></li>
</ul>]]></content><author><name>Y Zhang, K Yu,</name></author><summary type="html"><![CDATA[[C] — Training-Free Feature Reconstruction with Sparse Optimization for Vision-Language Models Y Zhang, K Yu, Arxiv-Link]]></summary><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/07/mm24b.png" /><media:content medium="image" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/07/mm24b.png" xmlns:media="http://search.yahoo.com/mrss/" /></entry><entry><title type="html">NODE-Adapter: Neural Ordinary Differential Equations for Better Vision-Language Reasoning</title><link href="http://0.0.0.0:4000/2024/07/01/tmm4.html" rel="alternate" type="text/html" title="NODE-Adapter: Neural Ordinary Differential Equations for Better Vision-Language Reasoning" /><published>2024-07-01T00:00:00+00:00</published><updated>2024-10-28T18:15:30+00:00</updated><id>http://0.0.0.0:4000/2024/07/01/tmm4</id><content type="html" xml:base="http://0.0.0.0:4000/2024/07/01/tmm4.html"><![CDATA[<p>[P] — NODE-Adapter: Neural Ordinary Differential Equations for Better Vision-Language Reasoning<br />
Y Zhang, C-W Cheng, K Yu, Z He, C</p>
<ul>
<li><a href="https://arxiv.org/search/cs?searchtype=author&query=Schonlieb,+C">–</a></li>
<li><a href="https://arxiv.org/pdf/2407.08672">Arxiv-Link </a></li>
</ul>]]></content><author><name>Y Zhang, C-W Cheng, K Yu, Z He, C</name></author><summary type="html"><![CDATA[[P] — NODE-Adapter: Neural Ordinary Differential Equations for Better Vision-Language Reasoning Y Zhang, C-W Cheng, K Yu, Z He, C – Arxiv-Link ]]></summary><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/07/tmm4.png" /><media:content medium="image" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/07/tmm4.png" xmlns:media="http://search.yahoo.com/mrss/" /></entry><entry><title type="html">Deep Block Proximal Linearised Minimisation Algorithm for Non-convex Inverse Problems</title><link href="http://0.0.0.0:4000/2024/06/01/deepblock.html" rel="alternate" type="text/html" title="Deep Block Proximal Linearised Minimisation Algorithm for Non-convex Inverse Problems" /><published>2024-06-01T00:00:00+00:00</published><updated>2024-10-28T18:15:30+00:00</updated><id>http://0.0.0.0:4000/2024/06/01/deepblock</id><content type="html" xml:base="http://0.0.0.0:4000/2024/06/01/deepblock.html"><![CDATA[<p>[P] — Deep Block Proximal Linearised Minimisation Algorithm for Non-convex Inverse Problems<br />
C Huang, Z Wu, Y Cheng, T Zheng, C</p>
<ul>
<li><a href="https://arxiv.org/search/cs?searchtype=author&query=Schonlieb,+C">–</a></li>
<li><a href="https://arxiv.org/pdf/2406.02458">Arxiv-Link </a></li>
</ul>]]></content><author><name>C Huang, Z Wu, Y Cheng, T Zheng, C</name></author><summary type="html"><![CDATA[[P] — Deep Block Proximal Linearised Minimisation Algorithm for Non-convex Inverse Problems C Huang, Z Wu, Y Cheng, T Zheng, C – Arxiv-Link ]]></summary><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/06/deepblock.png" /><media:content medium="image" url="https://angelicaiaviles.wordpress.com/wp-content/uploads/2024/06/deepblock.png" xmlns:media="http://search.yahoo.com/mrss/" /></entry></feed>