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Quantum ML
Добавлен 27 дек 2019
Quantum Machine Learning - 39 - Using Quantum Linear Algebra for Learning
Quantum Machine Learning MOOC, created by Peter Wittek from the University of Toronto in Spring 2019.
Lecture 39: Using Quantum Linear Algebra for Learning
Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us!
Full Playlist: ruclips.net/p/PLmRxgFnCIhaMgvot-Xuym_hn69lmzIokg
Link to the official EdX course: courses.edx.org/courses/course-v1:University_of_TorontoX+UTQML101x+1T2019/course/
Lecture 39: Using Quantum Linear Algebra for Learning
Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us!
Full Playlist: ruclips.net/p/PLmRxgFnCIhaMgvot-Xuym_hn69lmzIokg
Link to the official EdX course: courses.edx.org/courses/course-v1:University_of_TorontoX+UTQML101x+1T2019/course/
Просмотров: 4 126
Видео
Quantum Machine Learning - 41 - Guest lecture by Seth Lloyd
Просмотров 8 тыс.4 года назад
Quantum Machine Learning MOOC, created by Peter Wittek from the University of Toronto in Spring 2019. Lecture 41: Quantum Machine Learning (Guest lecture Seth Lloyd) Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us! Full Playlist: ruclips.net/p/PL...
Quantum Machine Learning - 40 - Quantum-Assisted Gaussian Processes
Просмотров 2,8 тыс.4 года назад
Quantum Machine Learning MOOC, created by Peter Wittek from the University of Toronto in Spring 2019. Lecture 40: Quantum-Assisted Gaussian Processes Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us! Full Playlist: ruclips.net/p/PLmRxgFnCIhaMgvot-...
Quantum Machine Learning - 38 - Quantum Matrix Inversion
Просмотров 3,6 тыс.4 года назад
Quantum Machine Learning MOOC, created by Peter Wittek from the University of Toronto in Spring 2019. Lecture 38: Quantum Matrix Inversion Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us! Full Playlist: ruclips.net/p/PLmRxgFnCIhaMgvot-Xuym_hn69lm...
Quantum Machine Learning - 37 - Overview of the HHL Algorithm
Просмотров 9 тыс.4 года назад
Quantum Machine Learning MOOC, created by Peter Wittek from the University of Toronto in Spring 2019. Lecture 37: Overview of the HHL Algorithm Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us! Full Playlist: ruclips.net/p/PLmRxgFnCIhaMgvot-Xuym_h...
Quantum Machine Learning - 36 - Quantum Phase Estimation
Просмотров 6 тыс.4 года назад
Quantum Machine Learning MOOC, created by Peter Wittek from the University of Toronto in Spring 2019. Lecture 36: Quantum Phase Estimation Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us! Full Playlist: ruclips.net/p/PLmRxgFnCIhaMgvot-Xuym_hn69lm...
Quantum Machine Learning - 32 - Quantum-Enhanced Kernel Methods 1 (Maria Schuld)
Просмотров 9 тыс.4 года назад
Quantum Machine Learning MOOC, created by Peter Wittek from the University of Toronto in Spring 2019. Lecture 32: Quantum-Enhanced Kernel Methods 1 (Guest lecture by Maria Schuld) Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us! Full Playlist: ru...
Quantum Machine Learning - 35 - Quantum Fourier Transform
Просмотров 6 тыс.4 года назад
Quantum Machine Learning MOOC, created by Peter Wittek from the University of Toronto in Spring 2019. Lecture 35: Quantum Fourier Transform Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us! Full Playlist: ruclips.net/p/PLmRxgFnCIhaMgvot-Xuym_hn69l...
Quantum Machine Learning - 33 - Quantum-Enhanced Kernel Methods 2 (Maria Schuld)
Просмотров 4,2 тыс.4 года назад
Quantum Machine Learning MOOC, created by Peter Wittek from the University of Toronto in Spring 2019. Lecture 33: Quantum-Enhanced Kernel Methods 2 (Guest lecture by Maria Schuld) Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us! Full Playlist: ru...
Quantum Machine Learning - 34 - Quantum-Enhanced Kernel Methods 3 (Maria Schuld)
Просмотров 4,3 тыс.4 года назад
Quantum Machine Learning MOOC, created by Peter Wittek from the University of Toronto in Spring 2019. Lecture 34: Quantum-Enhanced Kernel Methods 3 (Guest lecture by Maria Schuld) Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us! Full Playlist: ru...
Quantum Machine Learning - 31 - Optimization and Sampling in PGMs
Просмотров 2,2 тыс.4 года назад
Quantum Machine Learning MOOC, created by Peter Wittek from the University of Toronto in Spring 2019. Lecture 31: Optimization and Sampling in PGMs Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us! Full Playlist: ruclips.net/p/PLmRxgFnCIhaMgvot-Xu...
Quantum Machine Learning - 30 - Probabilistic Graphical Models
Просмотров 3,2 тыс.4 года назад
Quantum Machine Learning MOOC, created by Peter Wittek from the University of Toronto in Spring 2019. Lecture 30: Probabilistic Graphical Models Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us! Full Playlist: ruclips.net/p/PLmRxgFnCIhaMgvot-Xuym_...
Quantum Machine Learning - 29 - An Interference Circuit
Просмотров 2,6 тыс.4 года назад
Quantum Machine Learning MOOC, created by Peter Wittek from the University of Toronto in Spring 2019. Lecture 29: An Interference Circuit Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us! Full Playlist: ruclips.net/p/PLmRxgFnCIhaMgvot-Xuym_hn69lmz...
Quantum Machine Learning - 28 - Kernel Methods
Просмотров 4,3 тыс.4 года назад
Quantum Machine Learning MOOC, created by Peter Wittek from the University of Toronto in Spring 2019. Lecture 28: Kernel Methods Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us! Full Playlist: ruclips.net/p/PLmRxgFnCIhaMgvot-Xuym_hn69lmzIokg Link...
Quantum Machine Learning - 27 - Clustering by Quantum Optimization
Просмотров 3,7 тыс.4 года назад
Quantum Machine Learning MOOC, created by Peter Wittek from the University of Toronto in Spring 2019. Lecture 27: Clustering by Quantum Optimization Peter disappeared in the Himalayas due to an avalanche in September 2019. I upload those videos as a tribute to him and his passion for open knowledge. Thanks Peter for everything you've done for us! Full Playlist: ruclips.net/p/PLmRxgFnCIhaMgvot-X...
Quantum Machine Learning - 26 - QBoost
Просмотров 3,2 тыс.4 года назад
Quantum Machine Learning - 26 - QBoost
Quantum Machine Learning - 25 - Ensemble Learning
Просмотров 3,5 тыс.4 года назад
Quantum Machine Learning - 25 - Ensemble Learning
Quantum Machine Learning - 24 - Encoding Classical Information
Просмотров 6 тыс.4 года назад
Quantum Machine Learning - 24 - Encoding Classical Information
Quantum Machine Learning - 21 - Variational Circuits and Quantum Simulation 2 (Alan Aspuru-Guzik)
Просмотров 3,9 тыс.4 года назад
Quantum Machine Learning - 21 - Variational Circuits and Quantum Simulation 2 (Alan Aspuru-Guzik)
Quantum Machine Learning - 20 - Variational Circuits and Quantum Simulation 1 (Alan Aspuru-Guzik).
Просмотров 6 тыс.4 года назад
Quantum Machine Learning - 20 - Variational Circuits and Quantum Simulation 1 (Alan Aspuru-Guzik).
Quantum Machine Learning - 23 - Variational Circuits and Quantum Simulation 4 (Alan Aspuru-Guzik)
Просмотров 3,5 тыс.4 года назад
Quantum Machine Learning - 23 - Variational Circuits and Quantum Simulation 4 (Alan Aspuru-Guzik)
Quantum Machine Learning - 22 - Variational Circuits and Quantum Simulation 3 (Alan Aspuru-Guzik)
Просмотров 5 тыс.4 года назад
Quantum Machine Learning - 22 - Variational Circuits and Quantum Simulation 3 (Alan Aspuru-Guzik)
Quantum Machine Learning - 19 - Sampling a Thermal State
Просмотров 4,3 тыс.4 года назад
Quantum Machine Learning - 19 - Sampling a Thermal State
Quantum Machine Learning - 18 - Quantum Approximate Optimization Algorithm (QAOA)
Просмотров 12 тыс.4 года назад
Quantum Machine Learning - 18 - Quantum Approximate Optimization Algorithm (QAOA)
Quantum Machine Learning - 17 - Implementations
Просмотров 4,6 тыс.4 года назад
Quantum Machine Learning - 17 - Implementations
Quantum Machine Learning - 16 - Quantum Annealing
Просмотров 8 тыс.4 года назад
Quantum Machine Learning - 16 - Quantum Annealing
Quantum Machine Learning - 15 - Adiabatic Quantum Computing
Просмотров 9 тыс.4 года назад
Quantum Machine Learning - 15 - Adiabatic Quantum Computing
Quantum Machine Learning - 14 - Gate-Model Quantum Computing
Просмотров 6 тыс.4 года назад
Quantum Machine Learning - 14 - Gate-Model Quantum Computing
Quantum Machine Learning - 13 - Strategies to Solve the Many-Body Problem (Roger Melko)
Просмотров 6 тыс.4 года назад
Quantum Machine Learning - 13 - Strategies to Solve the Many-Body Problem (Roger Melko)
Quantum Machine Learning - 12 - Many-Body Behavior of Spins (Roger Melko)
Просмотров 6 тыс.4 года назад
Quantum Machine Learning - 12 - Many-Body Behavior of Spins (Roger Melko)
Bode Bypass
Batz Shore
So the whole thing is just too new to mix together yet? We need way more powerful quantum computers to implement Deep learning algorithms into them?
Thanks,this course is pretty nice! (A student from USTB.)
Rest in peace sir, respect for you
It seems someone from behind the camera is trying to make him laugh
What a lovely explanation
Very fascinating
His body in the avalanche was never found. Presumed dead.
ruclips.net/video/rjxMaYvgbng/видео.html Lord Baruch Victorious Finality Patch Ultra Reality
U Shape Wave ruclips.net/video/wrBsqiE0vG4/видео.htmlsi=waT8lY2iX-wJdjO3 Thanks for your informative and well produced video. You and your viewers might find my quantum-like analog interesting and or useful. I have been trying to describe the “U” shape wave that is produced in my amateur science mechanical model in the video linked below. I hear if you over-lap wave together using Fournier Transforms, it may make a “U” shape or square wave. Can this be correct representation Feynman Path Integrals? In the model, “U” shape waves are produced as the loading increases and just before the wave-like function shifts to the next higher energy level. Your viewers might be interested in seeing the load verse deflection graph in white paper found elsewhere on my RUclips channel. Actually replicating it with a sheet of clear folder plastic and tape and seeing it first hand is worth the effort.
4 electron integral or 2 electron integral? The second term 5:30
guy discarded theory saying that, "there is nothing quantum happening in it!"
Ntli?
Thank you
This is gotta be the best explanation.
What should \sigma_i^Z on the left side be for i=1,2? You only defined \sigma^Z.
\sigma_i^Z is \sigma^Z applied to the i-th qubit. Mathematically this is done by using the tensor product. If we denote by I the identity operator and by * the tensor product, we have: \sigma_i^Z = I * I * ...* I * \sigma^Z * I * .... * I, where \sigma^Z is the i-th operator. Assuming we only have 2 qubits, we can write \sigma_1^Z = I * \sigma^Z and \sigma_2^Z = \sigma^Z * I.
Which one do you think is the best architecture?
Sir, Bell states are mixed are pure state?
Bell states are pure 2 qubits states. I think you get confused between superpositions and mixed states
How to decompose b in terms of eigenvectors of A?
The best explanation series i have come across so far.
Best 👍 teaching approach
Thank you
hi i have a question can we use Quantum Machine Learning to make a new quantum algorithms?
In the phase estimation we assume that the register "b" is an eigenvector. And becuse of this the phase kickback works. Why the same technique (phase kickback) works here if "b" is definately not the eigenvector of unitary made from A?
what is the name of the book that she mentioned at 02:08 also at 06:25 ?
It's called 《Supervised Learning with Quantum Computers》
Thanks for the intuition!
Is he writing in a mirrored manner?
why are qubits distinguishable? bc they are based on superconducting circuits? what if we use cold atoms/ions which are naturally bosons(or fermions) and indistinguishable
He is always alive...Knowledge can not be killed...He is more alive then many people.
1:27 dagger means not complex but hermitian conjugated (h.c.)
this paper shows how one can get intrinsic equations between spin states independent from Js arxiv.org/pdf/0904.1470v1.pdf
this paper shows how one can get intrinsic equations between spin states independent from Js arxiv.org/pdf/0904.1470v1.pdf
Hearing you say systematically say "nuculus" instead of nucleus is distracting, bringing to mind Homer Simpson's famous quote.
Thanks for these simple excellent videos :) RIP 🥀
amazingly I got the concept of state encoding for my thesis. thanks Sir!
RIP
Thanks for the amazing content. I have one quick question: Can you confirm that that topic that you are converting is the same as converted on this paper "Quantum algorithms for training Gaussian Processes"? I have to do a review on this paper and It will be best if I just learn your presentation of the topic.
Thank you for this lecture!
Fascinating lecture! Thank you for posting this!
how do we design the circuit?
Thank you for explaining this so clearly, I am experimenting on D-Wave Quantum Computers that focuses on solving QUBO problem.
Thank You
Temporal mathematical approaches pertaining to quantum gravity analytics quantum entangled to quantum systems where the entropy from any wavefunction can be evolved in to never ending quantum algorithm gates ergo evertts universal wavefunction -(the multiverse but limited pertaining to said power user results implementation), can be exploited once humanity ascertains such quantum gravity processes. Many body holographic temporal quantum annealing, so to speak.
Holographic data storage / retrieval offers an endless array of potential infinite data storage potentially utilizing Morphia genetic field recovery methods synchronized with quantum algorithmic data retrieval whereas each frequency inherent to said hologram host quanta waiting to be activated with quantum entangled pulse injected code for security and so to flux the data recovery protocols pertaining to the quantum algorithm database hosted by the gate and so on.
The whole stuff is sooo cool! And all the professors are so great to explain hard concepts in an understandable way!
The best way to honor him is to really make the most of this 41 lectures!!! Thanks a lot!! RIP
Good leacture sir
I dont even know how classic computers work but this explanation is amazing!
You are great sir ❤️