#differentiableprogramming 搜尋結果
Learning the Effect of Persuasion via Difference-In-Differences. arxiv.org/abs/2410.14871
Interested in the impact that differentiable programming has had on Julia? Check out @_mbauman's talk at SPLASH Rebase 2020. Link: youtube.com/watch?v=rF2QAJ… #JuliaLang #OpenSource #DifferentiableProgramming
#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.
🎉 Today’s the day! Join the POEM Framework Webinar at 11AM. Learn strategies that helped companies like Omniretail, PowerStove & FlexiSAF 👉 Watch live: bit.ly/4mJZ2W5 #POEMFramework #DistinctionCourses #Startups #Entrepreneurship
A golden learning resource for introduction to deep neural networks and differentiable programming. "Alice's Adventures in a Differentiable Wonderland" ✨ - Automatic differentiation, stochastic optimization, and activation functions in depth and related core concepts. -…
Differentiable Digital Signal Processing (DDSP)! Fusing classic interpretable DSP with neural networks. ⌨️ Blog: magenta.tensorflow.org/ddsp 🎵 Examples: g.co/magenta/ddsp-e… ⏯ Colab: g.co/magenta/ddsp-d… 💻 Code: github.com/magenta/ddsp 📝 Paper: g.co/magenta/ddsp-p… 1/
Students can have differentiated assignments with @waygroundai by using the differentiaton tool, you can adjust reading level and number of questions. @AlanaColabella #letsfindaway
Pharmacophore model guided 3D molecular generation through diffusion model 1. A new framework called DiffPharm has been introduced for generating molecules that strictly satisfy 3D pharmacophore constraints, which is a significant challenge in de novo drug design. This framework…
I am proud to announce that we have just released difflogic, a PyTorch-based library for differentiable logic gate networks. Training is now around 50-100x faster than in our original NeurIPS 2022 paper code, as we provide heavily-optimized CUDA kernels. github.com/Felix-Petersen…
We called this a mile away. You can scrape all of the internet, but what if you plateau anyway? What you need is dynamic AI training that leverages real-time competition rather than static datasets. That’s how you build a self-improving ecosystem where AI models evolve through…
Crazy how you can say this when your whole mission is literally making the models better… muh AGI. “They’re not going to get much better… And never they’re going to get worse” -Sam Altman
Great work across 281-pages "Alice's Adventures in a Differentiable Wonderland" ✨ Brilliant introduction to deep neural networks and differentiable programming. Key areas covered ↓↓ • Automatic differentiation, stochastic optimization, and activation functions in depth…
Did you know: First-class differentiable programming in Swift lets you step over your code *backwards* using LLDB during backpropagation.
Visual generation is fully differentiable in continuous space. No RL is needed. RL is a necessary evil for the discrete nature of language. We show differentiable gradient feedback is more effective than RL under the same setting (SFT first) and it works when RL doesn't (no SFT)
Learn how leveraging #DiverseBackgrounds and unconventional combinations of ideas can drive #innovation and elevate #TeamPerformance in #leadership contexts. #DiverseThinkingIntegration #UnconventionalCollaborationCreativity #ChiefExecutive buff.ly/pHPXUM9
@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
"Differentiable" used to mean "df/dx is well-defined at all points in the domain of f". Now it seems to mean "there's a PyTorch library that purports to compute df/dx, even where it is not defined". And "non-differentiable" just means "nobody has written such a library yet".
The Elements of Differentiable Programming Mathieu Blondel, Vincent Roulet : arxiv.org/abs/2403.14606 #ArtificialIntelligence #DifferentiableProgramming #MachineLearning
Interested in creating your own automatically differentiable simulation code? My next ~100 line #Python tutorial explores how to do this using JAX. Writeup and code at the link: 👉 philip-mocz.medium.com/create-your-ow…
New post! Optimizing Tool Selection for LLM Workflows: Differentiable Programming with @PyTorch and @DSPyOSS Training local, learnable routers can reduce token overhead, lower costs, and bring structure back to agentic workflows. This post shows how. (Link below)
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
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)
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
#control #barrierfunctions #differentiableprogramming #deeplearning #constraints #guarantees #safety
#differentiableprogramming #deeplearning #ai #control #opensource #code #reinforcementlearning #modelpredictivecontrol #stability #youtube #github
#differentiableprogramming #deeplearning #SciML #dynamicalsystems #control #ODE #Pytorch #video #programming
#ICYMI Learn how Facebook is using #Kotlin, developing a new #DifferentiableProgramming framework for it: bit.ly/3zH0D8f #transcript included #InfoQ #Java #JVMLanguages
Interested in the impact that differentiable programming has had on Julia? Check out @_mbauman's talk at SPLASH Rebase 2020. Link: youtube.com/watch?v=rF2QAJ… #JuliaLang #OpenSource #DifferentiableProgramming
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
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
#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.
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 ⚛️
Pokemon Grow with Neural Cellular Automata medium.com/the-scinder/pl… or rivesunder.github.io/cellular_autom… #cellularautomata #ArtificialIntelligence #differentiableprogramming #neuralnetworks
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]
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
#ICYMI Learn how Facebook is using #Kotlin, developing a new #DifferentiableProgramming framework for it: bit.ly/3zH0D8f #transcript included #InfoQ #Java #JVMLanguages
@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
Our next speaker at the #DifferentiableProgramming workshop at #NeurIPS21 is Karen Liu! Karen will speak about learnable physics models! 🤖
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! 🎲
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
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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