Merge pull request #10 from hls-fpga-machine-learning/jmduarte-patch-1

Update projects.html

Author: jmduarte

projects.html

@@ -48,16 +48,22 @@ <h2>Projects</h2>
 		<h3> Papers </h3>
 		<p style="line-height:1.3">
 			<ul>
-				<li> Fast inference of deep neural networks in FPGAs for particle physics, <a href="https://arxiv.org/abs/1804.06913"> arXiv </a> </li>
-				<li> FPGA-accelerated machine learning inference as a service for particle physics computing, <a href="https://arxiv.org/abs/1904.08986"> arXiv </a> </li>
+				<li> Fast inference of deep neural networks in FPGAs for particle physics, <a href="https://doi.org/10.1088/1748-0221/13/07/P07027">JINST 13, P07027 (2018)</a> </li>
+				<li> FPGA-accelerated machine learning inference as a service for particle physics computing, <a href="https://doi.org/10.1007/s41781-019-0027-2">Comput Softw Big Sci (2019) 3: 13</a> </li>
 			</ul>
 		</p>
 		<h3> Talks </h3>
 		<p style="line-height:1.3">
 		List of various presentations from the community<br>
 		<ul>
-			<li> xxx </li>
-			<li> xxx </li>
+			<li> K. Pedro, FPGA-accelerated machine learning inference as a service for particle physics computing, CHEP 2019, <a href="https://indico.cern.ch/event/773049/contributions/3474731/"><slides</a></li>
+			<li> J. Duarte, Machine Learning on FPGAs for low latency and high throughput inference, eScience 2019, <a href="https://escience2019.sched.com/event/Uuiy/machine-learning-on-fpgas-for-low-latency-and-high-throughput-inference?iframe=yes&w=100%&sidebar=yes&bg=no#">slides</a></li>
+			<li> M. Liu, FPGA-accelerated machine learning inference as a solution for particle physics computing challenges, PASC 2019, <a href="https://pasc19.pasc-conference.org/program/schedule/presentation/?id=msa134&sess=sess164">slides</a></li>
+			<li> J. Ngadiuba, hls4ml: deploying deep learning on FPGAs for trigger and data acquisition, ACAT 2019, <a href="https://indico.cern.ch/event/708041/contributions/3269690/">slides</a></li>
+			<li> J. Duarte, FPGA-accelerated machine learning inference for particle physics computing challenges, CTD 2019, <a href="https://indico.cern.ch/event/742793/contributions/3274392/">slides</a></li>
+			<li> J. Duarte, hls4ml: deploying deep learning on FPGAs for L1 trigger and data acquisition, TWEPP 2018, <a href="https://indico.cern.ch/event/697988/contributions/3055990/">slides</a></li>
+			<li> J. Ngadiuba, Synthesizing machine learning algorithms on FPGAs, CHEP 2018, <a href="https://indico.cern.ch/event/587955/contributions/2937529/">slides</a></li>
+			<li> N. Tran, Neural networks in FPGAs for trigger and DAQ, CTD 2018, <a href="https://indico.cern.ch/event/658267/contributions/2813688/">slides</a></li>
 		</ul>
 		</p>
 		</p>
@@ -68,4 +74,4 @@ <h3> Talks </h3>
 	<p>&copy; Untitled. All rights reserved. | Design by <a href="http://templated.co" rel="nofollow">TEMPLATED</a>.</p>
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