#differentiableprogramming résultats de recherche
#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.
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
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!
The Elements of Differentiable Programming Mathieu Blondel, Vincent Roulet : arxiv.org/abs/2403.14606 #ArtificialIntelligence #DifferentiableProgramming #MachineLearning
@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
A shoutout to Jax, pyhf, and neos in my talk at ICML on likelihoods #DifferentiableProgramming @iris_hep @lukasheinrich_ @phi_nate @lukasheinrich_ @kratsg
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
The Elements of Differentiable Programming Mathieu Blondel, Vincent Roulet : arxiv.org/abs/2403.14606 #ArtificialIntelligence #DifferentiableProgramming #MachineLearning
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
Our next speaker at the #DifferentiableProgramming workshop at #NeurIPS21 is Karen Liu! Karen will speak about learnable physics models! 🤖
Thanks @NVIDIA and @NVIDIAAI for accepting us in the Inception Program. Now, time to get a few more GPUs. #DeepLearning #DifferentiableProgramming #CUDA
#ICYMI Learn how Facebook is using #Kotlin, developing a new #DifferentiableProgramming framework for it: bit.ly/3zH0D8f #transcript included #InfoQ #Java #JVMLanguages
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 🌊🐠
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)
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 🔬🥼
#ICYMI What is #DifferentiableProgramming? It's a regular program, except it's parameterized, automatically differentiated, and trainable or optimizable. Learn how #Facebook is using #Kotlin, developing a new differentiable programming framework for it: bit.ly/3zH0D8f
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
Differentiable portfolio optimizers let you backpropagate through allocations. Train end-to-end asset allocation models using gradient descent. 📉 Optimization meets AI. #DifferentiableProgramming #AIInvesting
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]
Unveil Differentiable Programming. 📈🔧 Harness the power of differentiable functions in programming to enable automatic differentiation and optimization. #DifferentiableProgramming #AI #MachineLearning #DataScience #Aibrilliance. Learn More Courses at aibrilliance.com.
When you realize differentiable programming is the cool cousin of deep learning. 😎🤖 #TechTrends #DeepLearning #DifferentiableProgramming
🌐 Explore the power of differentiable programming! Learn how this emerging paradigm is transforming the way we develop computer programs and its impact on AI and machine learning. Credit to @MikeYoung #DifferentiableProgramming #AI #MachineLearning ift.tt/7J0ksx4
Dive into Differentiable Programming for advanced AI and machine learning. Unlock optimization and new possibilities. 🧠✨ #DifferentiableProgramming #AI #MachineLearning #LearnMore Learn More at aibrilliance.com
📜 Read #NewPaper: "Enhancing Spectroscopic Experiment Calibration through Differentiable Programming" by Fabrizio Napolitano. 🔗 See more details at: mdpi.com/2410-3896/9/2/… #spectroscopy #differentiableprogramming #energyscale #uncertainty #Xray #ML
"New study reveals the key elements of differentiable programming, shedding light on its potential for revolutionizing machine learning and optimization algorithms. #DifferentiableProgramming #MachineLearning #Optimization" bit.ly/3Vupl8P
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
Paper led by Wenceslao Shaw Cortez. experiments implemented using the Neuromancer SciML library in Pytorch: github.com/pnnl/neuromanc… #DPC #differentiableprogramming #safecontrol #barrierfunctions #PNNL
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
NeuroMANCER 1.4 release is out! What is new: 1, new simplified API for differentiable model-based policy optimization 2, more Google colab examples 3, improved environment installation github.com/pnnl/neuromanc… #opensource #differentiableprogramming #control #machinelearning
Our team is organizing a "Differentiable Programming for Modeling and Control of Dynamical Systems" workshop at the upcoming American Control Conference (ACC) held in sunny San Diego on May 30th. d-biswa.github.io/Differentiable… #differentiableprogramming #ACC23 #control #python #julia
New release of NeuroMANCER is out! github.com/pnnl/neuromanc… #opensource #differentiableprogramming #pytorch #optimization #control #dynamics
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!
Excited to introduce you to the first of many excellent speakers at #DifferentiableProgramming @NeurIPSConf! Adam Paszke (@apaszke) will speak about Dex and JAX!
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.
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
Our next speaker at the #DifferentiableProgramming workshop at #NeurIPS21 is Frank Noe (@FrankNoeBerlin)! Frank will speak about differentiabe programming in #MolecularPhysics ⚛️
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
Our next speaker at the #DifferentiableProgramming workshop at #NeurIPS21 is Sergey Ovchinnikov (@sokrypton)! Sergey will speak about differentiable programming for #ProteinSequences and #ProteinStructure 🔬🥼
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! 🎲
Pokemon Grow with Neural Cellular Automata medium.com/the-scinder/pl… or rivesunder.github.io/cellular_autom… #cellularautomata #ArtificialIntelligence #differentiableprogramming #neuralnetworks
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
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 🌊🐠
Our next speaker at the #DifferentiableProgramming workshop at #NeurIPS21 is Karen Liu! Karen will speak about learnable physics models! 🤖
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
@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
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]
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
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