Ph.D. candidate in BIT 2022-10-24T07:05:22.393Z https://yantijin.github.io/ Tijin Yan Hexo https://yantijin.github.io/2022/10/24/ICLR23-submitted-papers-list/ 2022-10-24T06:22:12.000Z 2022-10-24T07:05:22.393Z

<h1 id="ICLR23-submitted-paper-list"><a href="#ICLR23-submitted-paper-list" class="headerlink" title="ICLR23 submitted paper list"></a>ICLR23 submitted paper list</h1>

https://yantijin.github.io/2022/09/17/NeurIPS22%20accepted%20paper%20list/ 2022-09-17T07:31:23.000Z 2022-10-14T14:22:14.680Z

<h2 id="NeurIPS-22-accepted-papers-list"><a href="#NeurIPS-22-accepted-papers-list" class="headerlink" title="NeurIPS 22 accepted papers list"></a>NeurIPS 22 accepted papers list</h2>

https://yantijin.github.io/2022/06/19/ICML%202022%20accepted%20paper%20list/ 2022-06-19T14:31:08.000Z 2022-10-14T14:22:14.676Z

<h2 id="ICML-22-accepted-papers-list"><a href="#ICML-22-accepted-papers-list" class="headerlink" title="ICML 22 accepted papers list"></a>ICML 22 accepted papers list</h2>

https://yantijin.github.io/2022/06/06/Deep-Generative-Models/ 2022-06-06T14:35:40.000Z 2022-10-14T15:00:06.540Z

<h2 id="Deep-Generative-Models-VAE-Flow-Diffusion-GAN"><a href="#Deep-Generative-Models-VAE-Flow-Diffusion-GAN" class="headerlink" title="Deep Generative Models[VAE+Flow+Diffusion+GAN]"></a>Deep Generative Models[VAE+Flow+Diffusion+GAN]</h2>

https://yantijin.github.io/2021/11/12/ICLR%2022%20submitted%20papers/ 2021-11-12T09:02:08.000Z 2022-10-14T14:22:14.675Z

<h2 id="ICLR-22-submitted-papers-list"><a href="#ICLR-22-submitted-papers-list" class="headerlink" title="ICLR 22 submitted papers list"></a>ICLR 22 submitted papers list</h2>

https://yantijin.github.io/2021/11/07/NeurIPS%202021%20accepted%20paper%20list/ 2021-11-07T07:09:08.000Z 2022-10-14T14:22:14.680Z

<h2 id="NeurIPS-2021-accepted-paper-list"><a href="#NeurIPS-2021-accepted-paper-list" class="headerlink" title="NeurIPS 2021 accepted paper list"></a>NeurIPS 2021 accepted paper list</h2>

https://yantijin.github.io/2021/06/21/KDD2021%20Accepted%20Paper%20List/ 2021-06-21T07:30:05.000Z 2022-10-14T14:22:14.679Z

<h2 id="KDD2021-Accepted-Paper-List"><a href="#KDD2021-Accepted-Paper-List" class="headerlink" title="KDD2021 Accepted Paper List"></a>KDD2021 Accepted Paper List</h2>

https://yantijin.github.io/2021/06/06/ICML%202021%20accepted%20paper%20list/ 2021-06-06T10:09:08.000Z 2022-10-14T14:22:14.676Z

<h2 id="ICML-2021-accepted-paper-list"><a href="#ICML-2021-accepted-paper-list" class="headerlink" title="ICML 2021 accepted paper list"></a>ICML 2021 accepted paper list</h2>

https://yantijin.github.io/2021/01/15/ICLR2021/ 2021-01-15T12:09:08.000Z 2022-10-14T14:22:14.675Z

<h2 id="ICLR-2021-paper-list"><a href="#ICLR-2021-paper-list" class="headerlink" title="ICLR 2021 paper list "></a>ICLR 2021 paper list</h2>

https://yantijin.github.io/2021/01/03/AAAI%202021%20papers/ 2021-01-03T11:11:08.000Z 2022-10-14T14:22:14.625Z

<h2 id="AAAI-2021-papers"><a href="#AAAI-2021-papers" class="headerlink" title="AAAI 2021 papers"></a>AAAI 2021 papers</h2>

https://yantijin.github.io/2021/01/03/Dynamic-System-and-Optimal-Control-Perspective-of-Deep-Learning-Part-II/ 2021-01-03T02:50:03.000Z 2022-10-14T15:59:41.104Z

<h2 id="Dynamic-system-and-optimal-control-perspective-of-deep-learning-Part-II"><a href="#Dynamic-system-and-optimal-control-perspective-of-deep-learning-Part-II" class="headerlink" title="Dynamic system and optimal control perspective of deep learning (Part II)"></a>Dynamic system and optimal control perspective of deep learning (Part II)</h2>

https://yantijin.github.io/2020/12/29/GPU%E9%80%8F%E4%BC%A0%E6%95%99%E7%A8%8B/ 2020-12-29T13:05:01.000Z 2022-10-14T14:22:14.675Z

<h2 id="GPU透传教程"><a href="#GPU透传教程" class="headerlink" title="GPU透传教程"></a>GPU透传教程</h2>

https://yantijin.github.io/2020/11/15/NIPS20-paperlist/ 2020-11-15T03:45:08.000Z 2022-10-14T14:22:14.679Z

<h2 id="NeuraIPS’20"><a href="#NeuraIPS’20" class="headerlink" title="NeuraIPS’20"></a>NeuraIPS’20</h2>

https://yantijin.github.io/2020/11/15/Irregular-Time-Series-Papers/ 2020-11-15T03:37:08.000Z 2022-10-14T14:22:14.677Z

<p>本文将对于非周期采样时序数据的预测问题做一个初步的总结</p>

https://yantijin.github.io/2020/09/24/ODE%E6%95%B0%E5%80%BC%E8%A7%A3/ 2020-09-23T16:20:43.000Z 2022-10-14T14:22:14.681Z

<blockquote> <p>转载自 <strong>李森科在zhihu</strong> <a href="https://zhuanlan.zhihu.com/p/70255604">链接</a></p></blockquote>

https://yantijin.github.io/2020/09/23/%E7%A5%9E%E7%BB%8F%E4%BA%86%E7%9A%84ODE-Neural-CDE/ 2020-09-23T15:19:29.000Z 2022-10-14T14:22:14.704Z

<h3 id="Neural-Controlled-Differential-Equations-for-Irregular-Time-Series"><a href="#Neural-Controlled-Differential-Equations-for-Irregular-Time-Series" class="headerlink" title="Neural Controlled Differential Equations for Irregular Time Series"></a>Neural Controlled Differential Equations for Irregular Time Series</h3><blockquote> <p>Neural ODE的缺点是一旦初值确定，轨迹便确定，中间无法对轨迹进行修正，本文引入受控微分方程概念，使得后续拿到的数据得到进一步利用。<a href="http://arxiv.org/abs/2005.08926">ArXiv</a>, <a href="https://github.com/patrick-kidger/NeuralCDE">code</a>.</p></blockquote>

https://yantijin.github.io/2020/09/23/ODE%E5%9F%BA%E7%A1%80/ 2020-09-22T16:23:00.000Z 2022-10-14T14:22:14.681Z

<h2 id="一、基本概念"><a href="#一、基本概念" class="headerlink" title="一、基本概念"></a>一、基本概念</h2><p>在学习常微分方程之前，我们先了解一些基本的概念；我们在中学的时候都学过解方程（如： <img src="https://www.zhihu.com/equation?tex=x%5E2%2B5%3D0" alt="[公式]"> ），不过那都是函数方程（ <img src="https://www.zhihu.com/equation?tex=f%28x%29%3D0" alt="[公式]"> ，即含有未知数x的方程）。</p>

https://yantijin.github.io/2020/09/18/Dynamic-GNN-PaperList/ 2020-09-18T15:19:49.000Z 2022-10-14T14:22:14.646Z

<p>AAAI 2018:</p> <ul> <li>Dynamic Deep Neural Networks: Optimizing Accuracy-Efficiency Trade-offs by Selective Execution</li> <li>Dynamic Network Embedding by Modeling Triadic Closure Process</li> <li>DepthLGP: Learning Embeddings of Out-of-Sample Nodes in Dynamic Networks</li> </ul>

https://yantijin.github.io/2020/09/12/TS-Anomaly-Detection/ 2020-09-12T14:14:39.000Z 2022-10-14T14:22:14.682Z

<blockquote> <p>PaperList for TS anomaly detection</p></blockquote>

https://yantijin.github.io/2020/09/12/Dynamic-Systems-Paperlist/ 2020-09-12T05:29:52.000Z 2022-10-14T14:22:14.646Z

<blockquote> <p>PaperList For Dynamic systems with DNN</p></blockquote>