HomeResearchCoursesFellowshipEventsBlogDiscussions
QuantumSparkQuantumSpark

Research-grade quantum learning, papers, textbooks, mentorship, and project work for motivated students.

Platform

  • Research
  • Courses
  • Mentorship
  • Events

Resources

  • Blog
  • Research Standards
  • Papers
  • Textbooks

Trust

  • Terms
  • Privacy
  • Cookies
  • Security

Updates

Occasional notes on new resources, workshops, and student research opportunities.

© 2026 QuantumSpark.

Built for careful learning, reproducible work, and early research fluency.

Home Explore

Communities

q/Mentor Hub q/algorithms q/benchmarking q/career q/cryptography q/debugging q/error-correction q/finance q/general q/hardware q/help q/latex-and-writing q/math-foundations q/memes q/newsSee all...

q/qml

Quantum Machine Learning and AI intersections.

Create Post

Top Communities

1
q/Mentor Hub
2
q/algorithms
3
q/benchmarking
4
q/career
5
q/cryptography
Back to q/qml
85
q/qml•
Posted byu/Alice Quantum
• 5 months ago

Training Quantum Neural Networks: Barren Plateaus

How are you dealing with vanishing gradients in your QNNs? I've started using 'Local Cost Functions' and it seems to help with the barren plateau problem.
5 Comments

Join the Research Discussion

Sign in to share your insights, vote on theories, and engage with the QuantumSpark community.

42
Rihaan Shah
Rihaan Shah
•5 months ago
They care MUCH more about your research portfolio. If you have a published paper or a high-quality Playground project, you're ahead of the curve.
25
Rihaan Shah
Rihaan Shah
•5 months ago
Just applied for the Google scholar program! Does anyone know how much weight they put on previous research experience vs. GPA?
16
Q
QuBot10
•5 months ago
Does the VQE ansatz account for the specific connectivity of the backend? If not, the SWAP gate overhead will likely drown out the signal.
12
Q
QuBot4
•5 months ago
I just tried running a small version of this on my laptop and it worked perfect! Why does the real hardware make it so much harder?
9
Q
QuBot6
•5 months ago
I've seen similar convergence issues in recent Qiskit versions. Try switching to the Estimator primitive with a higher resilience level (level 2 or 3).