--- title: Neural Schedule: Learned Annealing Schedules | SpinForge url: https://spin-forge.com/synthesis/neural-schedule description: Learned temperature schedules for annealing through a Fourier neural operator. --- Synthesis / Layer 1 / C SPINFORGE / A GARMO LABS COMPANY # Neural Schedule Learned temperature schedules for annealing through a Fourier neural operator. [Explore the family](https://spin-forge.com/synthesis) [Talk about your workload](https://spin-forge.com/contact) Customer outcome [Design and discover](https://spin-forge.com/platform/discovery-design) THE PRODUCT, IN PRACTICE ## Learn the schedule. Evaluate the search. The schedule used by an annealing run influences how it explores a problem. Neural Schedule learns temperature schedules rather than relying only on manually selected heuristics. Its README describes a Fourier neural operator and makes a learned-versus-heuristic claim; a customer comparison retains the original workload and budget. BUILT FOR Optimization teams exploring learned control of annealing schedules. CHALLENGES PRODUCT RESPONSE ## The problem you face. What the product changes. YOUR CHALLENGE WITH NEURAL SCHEDULE 01 ### One schedule may not suit every workload Hand-selected temperature schedules can become another set of settings to tune. Neural Schedule learns the schedule used in the supported annealing workflow. 02 ### Training gains need a useful comparison A stronger result on development inputs need not carry to new inputs. Evaluate the learned schedule against the accepted heuristic under the same task and budget. 03 ### Schedule quality is not the whole run Training, inference and search contribute to the complete operating cost. Compare the accepted result and total cost rather than reporting only the schedule-generation step. WHAT YOU GET ## A defined capability. A useful result. 01 ### Learned temperature schedules A schedule-learning product built around an FNO. 02 ### An annealing control component Use the learned schedule in its supported optimization workflow. 03 ### Heuristic comparison scope Define the inputs and reference schedule used in acceptance. 04 ### A repeatable evaluation Retain the task, budget and appropriate result checks in the customer engagement. EXAMPLE CUSTOMER WORKFLOW ## Compare schedules on a problem family A team uses repeated annealing runs and wants to evaluate learned schedules. Illustrative customer use—not a new benchmark or completed customer deployment. 1. 01 Agree training and evaluation inputs and the reference heuristic. 2. 02 Run the supported learned-schedule workflow. 3. 03 Compare held-out quality, compute and checking cost. FIT & ACCEPTANCE ## Start with the task. Agree the useful outcome. What you bring The supported problem family, schedule-training inputs, reference heuristic and run budget. What a useful evaluation measures - + Accepted objective or task quality - + Held-out comparison at matched budget - + Full training and inference overhead Delivery License the selected capability, commission an implementation, or agree an operated service. Infrastructure and additional engineering are specified separately. QUESTIONS BEFORE BUYING ## A clear scope. A clear relationship. **What is the important boundary? − **“Learned > heuristic” is the README’s claim; no general performance multiplier or cross-domain superiority is asserted here. A learned schedule does not supply an optimality certificate by itself. **How is it priced? + **No new standalone price is supplied for this product; request a scoped proposal. The platform plans buy qualified workflows and capacity, not a second charge every time a compatible method is selected. Existing bundle inclusions do not expand automatically. **How do we get access? + **An existing product in the SpinForge portfolio. Request the release, available invocation interfaces and setup for your selected workflow; this publication does not invent executable commands or MCP tool names. PUT THE PRODUCT TO WORK ## Tell us what needs to improve. Bring a task, an accepted outcome and the environment in which the product needs to work. [Discuss this workflow ](https://spin-forge.com/contact?product=synthesis%2Fneural-schedule&brief=Product%3A+Neural+Schedule%0AOur+challenge%3A%0AOur+workload%2Finput%3A%0AExpected+result%3A%0AAcceptance%3A+Accepted+objective+or+task+quality%3B+Held-out+comparison+at+matched+budget%3B+Full+training+and+inference+overhead%0AEnvironment+and+delivery+preference%3A%0A) PRODUCT RELATIONSHIPS ## Related, not interchangeable. [Synthesis ### SpinForge Warp Differentiable annealing that lets a learning workflow backpropagate through optimization.](https://spin-forge.com/synthesis/warp) [Synthesis ### Gödel Optimizer A self-evolving optimizer that improves its optimization algorithms.](https://spin-forge.com/synthesis/godel-optimizer) [RELATED PRODUCT ### SpinForge + Atlas Optimization software for turning a supported decision model into a checked candidate solution, with execution planning included.](https://spin-forge.com/spinforge) ONE PLATFORM ## Choose a qualified workflow. Select the capability you need directly or include its compatible role in a qualified platform workflow. Production scope identifies release, environment, capacity and support; a product count is not an entitlement. [Explore monthly plans](https://spin-forge.com/plans) [See the system connections](https://spin-forge.com/system-synergies/product-map) START WITH THIS PRODUCT Use the software directly or ask us to scope the implementation. [Software access](https://spin-forge.com/plans?product=synthesis/neural-schedule) [Have us do the work](https://spin-forge.com/contact?product=synthesis/neural-schedule&delivery=engineering)