#differentiableprogramming search results
Newton's method is not efficient for automatic differentiation! Here's a quick explanation as a #sciml fun fact of the day #julialang #differentiableprogramming #automaticdifferentiation
#DifferentiableProgramming also allows us to compute the Jacobian of the steady-state with respect to any parameter of the Liouvillian. We did a sensitivity analysis of ρss with respect to the pumping rate (r) for a V-system.
@karpathy gives an overview of the history of programming and Computer Vision, and how they lead to Software 2.0 (aka #DifferentiableProgramming) at Scaled ML by @matroid
Learn to solve constrained optimization problems with hard constraints using differentiable projected gradient layers. See the Colab example implementing the method in Neuromancer: colab.research.google.com/github/pnnl/ne… #differentiableprogramming #optimization #constraints #opensource #PNNL
The Elements of Differentiable Programming Mathieu Blondel, Vincent Roulet : arxiv.org/abs/2403.14606 #ArtificialIntelligence #DifferentiableProgramming #MachineLearning
The Elements of Differentiable Programming Mathieu Blondel, Vincent Roulet : arxiv.org/abs/2403.14606 #ArtificialIntelligence #DifferentiableProgramming #MachineLearning
A shoutout to Jax, INFERNO, pyhf, and neos in my talk at ICML on likelihoods #DifferentiableProgramming @pablodecm @dorigo @iris_hep @lukasheinrich_ @phi_nate @lukasheinrich_ @kratsg
A shoutout to Jax, pyhf, and neos in my talk at ICML on likelihoods #DifferentiableProgramming @iris_hep @lukasheinrich_ @phi_nate @lukasheinrich_ @kratsg
Excited to introduce you to the first of many excellent speakers at #DifferentiableProgramming @NeurIPSConf! Adam Paszke (@apaszke) will speak about Dex and JAX!
Our next speaker at the #DifferentiableProgramming workshop at #NeurIPS21 is Karen Liu! Karen will speak about learnable physics models! 🤖
The Elements of Differentiable Programming Mathieu Blondel, Vincent Roulet : arxiv.org/abs/2403.14606 #ArtificialIntelligence #DifferentiableProgramming #MachineLearning
It's happening tomorrow!😱 Come join us at the #DifferentiableProgramming workshop @NeurIPSConf at 2pm GMT / 9am EST / 10pm CST, 13 Dec❗️ We are thrilled to see @apaszke @yuaanzhou @FrankNoeBerlin @KenoFischer @PatrickHeimbach Karen Liu @sokrypton Harshitha Menon, and all of you!
Our next speaker at the #DifferentiableProgramming workshop at #NeurIPS21 is Frank Noe (@FrankNoeBerlin)! Frank will speak about differentiabe programming in #MolecularPhysics ⚛️
Our next speaker at the #DifferentiableProgramming workshop at #NeurIPS21 is Sergey Ovchinnikov (@sokrypton)! Sergey will speak about differentiable programming for #ProteinSequences and #ProteinStructure 🔬🥼
Our next speaker at the #DifferentiableProgramming workshop at #NeurIPS21 is Patrick Heimbach (@PatrickHeimbach)! Patrick will speak about learning from data through the lens of #ocean models, surrogates, and their derivatives 🌊🐠
#ICYMI Learn how Facebook is using #Kotlin, developing a new #DifferentiableProgramming framework for it: bit.ly/3zH0D8f #transcript included #InfoQ #Java #JVMLanguages
Thanks @NVIDIA and @NVIDIAAI for accepting us in the Inception Program. Now, time to get a few more GPUs. #DeepLearning #DifferentiableProgramming #CUDA
Absolute pleasure to introduce our final speaker at the #DifferentiableProgramming workshop @NeurIPSConf 2021: Yuan Zhou (@yuaanzhou)! Yuan will speak about symbolic parallel adaptive importance sampling for #ProbabilisticProgramming analysis! 🎲
"new projects dispense with #computationgraph-s entirely, to bring #differentiableprogramming to the mainstream" "#Julia is unusually well-suited for expressing #machinelearning algorithm" "#SPMD programming" #automaticDifferentiation #automaticBatching #CompilerDesign #ML #DSL
A follow up from the "On Machine Learning and Programming Languages" blog from last year. We have made a bunch of progress and summarize it in a new post "Building a language and compiler for machine learning". julialang.org/blog/2018/12/m…
The Elements of Differentiable Programming Mathieu Blondel, Vincent Roulet : arxiv.org/abs/2403.14606 #ArtificialIntelligence #DifferentiableProgramming #MachineLearning
The Elements of Differentiable Programming Mathieu Blondel, Vincent Roulet : arxiv.org/abs/2403.14606 #ArtificialIntelligence #DifferentiableProgramming #MachineLearning
The Elements of Differentiable Programming Mathieu Blondel, Vincent Roulet : arxiv.org/abs/2403.14606 #ArtificialIntelligence #DifferentiableProgramming #MachineLearning
#DifferentiableProgramming also allows us to compute the Jacobian of the steady-state with respect to any parameter of the Liouvillian. We did a sensitivity analysis of ρss with respect to the pumping rate (r) for a V-system.
Learn to solve constrained optimization problems with hard constraints using differentiable projected gradient layers. See the Colab example implementing the method in Neuromancer: colab.research.google.com/github/pnnl/ne… #differentiableprogramming #optimization #constraints #opensource #PNNL
Excited to introduce you to the first of many excellent speakers at #DifferentiableProgramming @NeurIPSConf! Adam Paszke (@apaszke) will speak about Dex and JAX!
It's happening tomorrow!😱 Come join us at the #DifferentiableProgramming workshop @NeurIPSConf at 2pm GMT / 9am EST / 10pm CST, 13 Dec❗️ We are thrilled to see @apaszke @yuaanzhou @FrankNoeBerlin @KenoFischer @PatrickHeimbach Karen Liu @sokrypton Harshitha Menon, and all of you!
Our next speaker at the #DifferentiableProgramming workshop at #NeurIPS21 is Frank Noe (@FrankNoeBerlin)! Frank will speak about differentiabe programming in #MolecularPhysics ⚛️
Our next speaker at the #DifferentiableProgramming workshop at #NeurIPS21 is Sergey Ovchinnikov (@sokrypton)! Sergey will speak about differentiable programming for #ProteinSequences and #ProteinStructure 🔬🥼
Thanks @NVIDIA and @NVIDIAAI for accepting us in the Inception Program. Now, time to get a few more GPUs. #DeepLearning #DifferentiableProgramming #CUDA
A shoutout to Jax, pyhf, and neos in my talk at ICML on likelihoods #DifferentiableProgramming @iris_hep @lukasheinrich_ @phi_nate @lukasheinrich_ @kratsg
A shoutout to Jax, INFERNO, pyhf, and neos in my talk at ICML on likelihoods #DifferentiableProgramming @pablodecm @dorigo @iris_hep @lukasheinrich_ @phi_nate @lukasheinrich_ @kratsg
Pokemon Grow with Neural Cellular Automata medium.com/the-scinder/pl… or rivesunder.github.io/cellular_autom… #cellularautomata #ArtificialIntelligence #differentiableprogramming #neuralnetworks
#ICYMI Learn how Facebook is using #Kotlin, developing a new #DifferentiableProgramming framework for it: bit.ly/3zH0D8f #transcript included #InfoQ #Java #JVMLanguages
Interested in how #DifferentiableProgramming helps when it comes to complex computational models? Then you'll want to check out @Analyticsindiam's video of a keynote by Viral B Shah. Watch it now at: bit.ly/2KPkSIi #computing #rebootingcomputing
@karpathy gives an overview of the history of programming and Computer Vision, and how they lead to Software 2.0 (aka #DifferentiableProgramming) at Scaled ML by @matroid
Absolute pleasure to introduce our final speaker at the #DifferentiableProgramming workshop @NeurIPSConf 2021: Yuan Zhou (@yuaanzhou)! Yuan will speak about symbolic parallel adaptive importance sampling for #ProbabilisticProgramming analysis! 🎲
Our next speaker at the #DifferentiableProgramming workshop at #NeurIPS21 is Karen Liu! Karen will speak about learnable physics models! 🤖
Open-Source & Ready to Use! STLCG++ is available in JAX & PyTorch for easy integration into ML & robotics workflows. Try our STLCG++ trajectory optimization demo in GRID! 🔗grid.scaledfoundations.ai/shared/0c1a5a9… #Robotics #AI #DifferentiableProgramming #Neurosymbolic [8/n]
![Parvkpr's tweet image. Open-Source & Ready to Use! STLCG++ is available in JAX & PyTorch for easy integration into ML & robotics workflows.
Try our STLCG++ trajectory optimization demo in GRID! 🔗grid.scaledfoundations.ai/shared/0c1a5a9…
#Robotics #AI #DifferentiableProgramming #Neurosymbolic
[8/n]](https://pbs.twimg.com/media/GlxU5YfWQAASNcm.jpg)
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